49 lines
215 KiB
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49 lines
215 KiB
Text
{"parentUuid":null,"isSidechain":true,"promptId":"a8c573a5-ab53-4aa9-b96e-0cc4596f62d1","agentId":"ad972fd5e7bb2dd5a","type":"user","message":{"role":"user","content":"You are an adversarial CODE + REASONING auditor. Do NOT trust the author. Ground every claim in file:line. Do NOT read .env. No paid model calls — $0 static analysis only.\n\n## Target 1: audit the harness code for BUGS that would corrupt its numbers\nFile: `/home/ubuntu/projects/textmachine/eval/softsign-decl/main.go` (a Go $0 probe).\nIt measures whether a glossary term's Russian `dst` appears in model output, accepting declined forms, under 4 rules (A0 live / A1 naive-«ь» / A2 anchor-exact / A3 anchor-normal-stem). It reuses the shipped stemmer `lang.TargetStemmer` (`/home/ubuntu/projects/textmachine/backend/internal/lang/stemmer.go`, read it). The A0 path is meant to be a faithful port of `backend/internal/membank/mempostcheck.go` functions `declinedFormPresent` (lines 169-191), `dstFormPresent` (146-164), `containsWholeWord` (197-211) — read those and diff against the harness.\n\nHunt specifically for:\n1. **`stemAug` correctness** (main.go ~line 40): does it FAITHFULLY model \"add «ь» to the decl_suffix registry, longest-first\"? The real `Stem` (stemmer.go:49) strips the LONGEST listed suffix leaving stem>=3. Is there a word where real-registry-with-«ь» would strip a DIFFERENT suffix than `stemAug` produces? Consider words ending in a listed multi-rune suffix that is ALSO reachable after a «ь». Consider the `minStemRunes=3` boundary (len>=4 check).\n2. **`windowMatch` anchor logic** (~line 90): A2 requires `soft[k] && anyExact`, A3 `soft[k] && anyNorm`. Is `anyExact`/`anyNorm` computed over the WHOLE window incl. position k itself? Can a component be its OWN anchor (a bug — a soft-only match self-licensing)? Trace: if position k matches ONLY via soft (norm[k]=false, exact[k]=false), can `anyNorm`/`anyExact` still be true from k? Confirm the anchor must be a DIFFERENT component.\n3. **`present`/`countWindows`/`firstWindowText`**: off-by-one in window bounds `i+n <= len`; does A0 via this path equal real `dstFormPresent` (base whole-word OR declined)?\n4. **`containsWholeWord` port** vs mempostcheck.go:197-211 — rune-boundary logic identical? Does it use `text.RunesEqual` semantics correctly (the harness inlines a rune loop)?\n5. **`loadBankDst`**: header skip, tab split, dedup — could it mis-parse BANK-FULL.tsv (col2=dst) and drop/duplicate rows? (bank has 151 lines, harness reports 147 uniq dst.)\n6. Tokenization: harness uses `lang.TokenizeWords` (delegates to `text.TokenizeLetters`) for both base and output — same as production `Postcheck`? Any normalization mismatch (`text.NormalizeTargetForm`)?\n\n## Target 2: adversarially challenge the author's RECOMMENDATION\nThe author concluded: (1) close the gap via SEED decl-enumeration for soft-final SIGNED-CANON names (Фан Юань, Винный червь) — declForms match exactly via containsWholeWord, zero collision; (2) do NOT build the engine anchor-gated soft match now (it relocates the Синь/Линь collision to [title]+[ь-surname] shape and doesn't protect the number class); (3) defer engine mechanism to a 2nd book. Attack this:\n- Is seed-enumeration actually clean/bounded, or does it re-introduce the \"142/142-null\" manual-decl-form toil that the §3 stemmer (`mempostcheck.go:20-29`) exists to KILL? How many forms per name, and who fills them (is it manual seed toil or mineable)? Read `backend/internal/pipeline/seeding.go` and any seed schema for `declForms`/decl.\n- Does the recommendation smuggle book-specifics into a place that breaks the generality invariant (engine Go must not branch on pair/book; book-canon → seed/brief data)? Is seed declForms the RIGHT data home, or does it belong in the bank-miner?\n- Is \"defer\" honest, or is it avoiding a real recurring cost? The measured per-chunk false-miss is ~4-26/25ch (proxy). Argue whether that's worth ZERO action vs the seed cost.\n- Steelman the OPPOSITE: that the engine anchor-gated match SHOULD be built now (with the number-class stoplist + tail-restriction). What's the strongest case for it?\n\nDeliverable: terse findings list. Each: CONFIRMED-BUG (file:line + the input that breaks it) / NO-BUG (what you checked) for Target 1; and for Target 2, the single strongest counter to the recommendation. End with a one-line verdict: are the harness numbers TRUSTWORTHY, and is the recommendation SOUND or should it change?"},"uuid":"c75f6ffa-c7b1-4042-8964-d05ef1a6c3e0","timestamp":"2026-08-01T15:19:01.598Z","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"6bafbdd7-a38e-4de3-9926-4504c6a6f7be","isSidechain":true,"agentId":"ad972fd5e7bb2dd5a","attachment":{"type":"skill_listing","content":"- dataviz: Use this skill whenever you are about to create ANY chart, graph, plot, dashboard, or data visualization, in ANY output medium — an HTML or React artifact, inline SVG, plotting code in any library (matplotlib, plotly, d3, Recharts, …), an image/PNG you will render and upload, or a chart shared into Slack. Read it BEFORE writing the first line of chart code, choosing chart colors, building a stat tile / meter / KPI row, or laying out a dashboard. Produces visualizations that read as one system — elegant, accessible, consistent in light and dark — using a brand-neutral placeholder palette you swap for your own. Teaches a design-system-agnostic method: a form heuristic, a color formula with a runnable validator, mark specs, and interaction rules. A validated default palette is documented in `references/palette.md` — swap that file's values for your brand's. Triggers on: \"chart\", \"graph\", \"plot\", \"data viz\", \"visualization\", \"dashboard\", \"analytics\", \"visualize data\", \"categorical colors\", \"sequential / diverging palette\", \"stat tile\", \"sparkline\", \"heatmap\", \"legend\", \"axis\", \"tooltip\", \"chart colors\", \"color by series\".\n- artifact-design: Design guidance and fundamentals for Artifacts.\n- artifact-capabilities: Runtime capabilities a published Artifact page can be granted — behavior static HTML cannot provide on its own, such as the page reading live or connected data, keeping state shared across viewers, or updating and republishing itself. Serves this user's live capability roster and the typed call definitions. Load it whenever the user asks for an artifact needing any such runtime behavior.\n- update-config: Use this skill to configure the Claude Code harness via settings.json. Automated behaviors (\"from now on when X\", \"each time X\", \"whenever X\", \"before/after X\") require hooks configured in settings.json - the harness executes these, not Claude, so memory/preferences cannot fulfill them. Also use for: permissions (\"allow X\", \"add permission\", \"move permission to\"), env vars (\"set X=Y\"), hook troubleshooting, or any changes to settings.json/settings.local.json files. Examples: \"allow npm commands\", \"add bq permission to global settings\", \"move permission to user settings\", \"set DEBUG=true\", \"when claude stops show X\". For simple settings like theme/model, suggest the /config command.\n- keybindings-help: Use when the user wants to customize keyboard shortcuts, rebind keys, add chord bindings, or modify ~/.claude/keybindings.json. Examples: \"rebind ctrl+s\", \"add a chord shortcut\", \"change the submit key\", \"customize keybindings\".\n- simplify: Review the changed code for reuse, simplification, efficiency, and altitude cleanups, then apply the fixes. Quality only — it does not hunt for bugs; use /code-review for that.\n- fewer-permission-prompts: Scan your transcripts for common read-only Bash and MCP tool calls, then add a prioritized allowlist to project .claude/settings.json to reduce permission prompts.\n- loop: Run a prompt or slash command on a recurring interval (e.g. /loop 5m /foo). Omit the interval to let the model self-pace. - When the user wants to set up a recurring task, poll for status, or run something repeatedly on an interval (e.g. \"check the deploy every 5 minutes\", \"keep running /babysit-prs\"). Do NOT invoke for one-off tasks.\n- schedule: Create, update, list, or run scheduled cloud agents (routines) that execute on a cron schedule. - When the user wants to schedule a recurring cloud agent, set up automated tasks, create a cron job for Claude Code, or manage their scheduled agents/routines. Also use when the user wants a one-time scheduled run (\"run this once at 3pm\", \"remind me to check X tomorrow\").\n- claude-api: Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration.\nTRIGGER — read BEFORE opening the target file; don't skip because it \"looks like a one-liner\" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens).\nSKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).\n- run: Launch and drive this project's app to see a change working. Use when asked to run, start, or screenshot the app, or to confirm a change works in the real app (not just tests). First looks for a project skill that already covers launching the app; otherwise falls back to built-in patterns per project type (CLI, server, TUI, Electron, browser-driven, library).\n- init: Initialize a new CLAUDE.md file with codebase documentation\n- review: Review a GitHub pull request; for your working diff use /code-review\n- security-review: Complete a security review of the pending changes on the current branch","skillCount":14,"isInitial":true,"names":["dataviz","artifact-design","artifact-capabilities","update-config","keybindings-help","simplify","fewer-permission-prompts","loop","schedule","claude-api","run","init","review","security-review"]},"type":"attachment","uuid":"99bd1bc7-3335-4922-8ce7-2d102b8c9ed3","timestamp":"2026-08-01T15:19:01.604Z","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"89836c21-46de-4a6d-a2f6-238de1029b5b","isSidechain":true,"promptId":"a8c573a5-ab53-4aa9-b96e-0cc4596f62d1","agentId":"ad972fd5e7bb2dd5a","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01NF6B66ku28v6SThnFUYFcD","type":"tool_result","content":"1\t// Command softsign-decl измеряет разрыв мягкого знака в декл-пост-чеке банка (fix-pack §а finding-1) на\n2\t// БОЕВОМ стеммере, НЕ ТРОГАЯ репозиторий. Прецедент — pkg6 `labels/` и pkg7 `minerharness`: отдельный\n3\t// Go-модуль ВНЕ репо с `module textmachine/backend/<имя>` и `replace textmachine/backend => <пин-копия>`;\n4\t// имя обязано начинаться с `textmachine/backend/`, иначе Go запретит импорт `internal/`. Сборка/пин —\n5\t// `build.sh` (git archive <commit>), чтобы незакоммиченные правки параллельных сессий не меняли результат.\n6\t//\n7\t// Что мерит: для каждого dst банка — приходит ли ПРИНЯТАЯ форма в боевой 25-глав-выход, под четырьмя\n8\t// правилами матчинга декл-окна:\n9\t// A0 — БОЕВОЕ поведение: declinedFormPresent (mempostcheck.go:169-191) — «ь» НЕ стрипается.\n10\t// A1 — наивное: «ь» добавлен в реестр стрипа, применяется к КАЖДОМУ компоненту, БЕЗ якоря (отвергнутый).\n11\t// A2 — anchor-gated: мягкий стрип на компоненте разрешён, если ДРУГОЙ компонент совпал ТОЧНО.\n12\t// A3 — anchor-gated: мягкий стрип разрешён, если ДРУГОЙ компонент совпал по НОРМАЛЬНОМУ стему (⊇ A2).\n13\t// A0 — построчный порт боевого кода на экспортных символах lang; паритет с реальным (unexported)\n14\t// dstFormPresent сверен отдельно в membank-пробе (0/29 расхождений) до порта. Ноль сети, ноль моделей, $0.\n15\tpackage main\n16\t\n17\timport (\n18\t\t\"flag\"\n19\t\t\"fmt\"\n20\t\t\"os\"\n21\t\t\"sort\"\n22\t\t\"strings\"\n23\t\t\"unicode\"\n24\t\n25\t\t\"textmachine/backend/internal/lang\"\n26\t\t\"textmachine/backend/internal/text\"\n27\t)\n28\t\n29\ttype mode int\n30\t\n31\tconst (\n32\t\tmodeA0 mode = iota\n33\t\tmodeA1\n34\t\tmodeA2\n35\t\tmodeA3\n36\t)\n37\t\n38\t// stemAug моделирует «добавить голый «ь» в реестр decl_suffix»: стрипнуть длиннейший реестровый суффикс;\n39\t// если ничего не стрипнуто, а слово кончается на «ь» и стем остаётся ≥ minStemRunes(3), стрипнуть «ь».\n40\t// Зеркалит longest-first (реальный суффикс всегда бьёт 1-руновый «ь»).\n41\tfunc stemAug(s lang.TargetStemmer, w string) string {\n42\t\tw = strings.ToLower(w)\n43\t\tif st := s.Stem(w); st != w {\n44\t\t\treturn st\n45\t\t}\n46\t\tr := []rune(w)\n47\t\tif len(r) >= 4 && r[len(r)-1] == 'ь' {\n48\t\t\treturn string(r[:len(r)-1])\n49\t\t}\n50\t\treturn w\n51\t}\n52\t\n53\tfunc softSameStem(s lang.TargetStemmer, a, b string) bool {\n54\t\tla, lb := strings.ToLower(a), strings.ToLower(b)\n55\t\tif la == lb {\n56\t\t\treturn true\n57\t\t}\n58\t\treturn stemAug(s, la) == stemAug(s, lb)\n59\t}\n60\t\n61\t// containsWholeWord — порт mempostcheck.go:197-211 (буквенная граница на обоих концах, по рунам).\n62\tfunc containsWholeWord(hay, form []rune) bool {\n63\t\tn := len(form)\n64\t\tif n == 0 || n > len(hay) {\n65\t\t\treturn false\n66\t\t}\n67\t\tfor i := 0; i+n <= len(hay); i++ {\n68\t\t\teq := true\n69\t\t\tfor k := 0; k < n; k++ {\n70\t\t\t\tif hay[i+k] != form[k] {\n71\t\t\t\t\teq = false\n72\t\t\t\t\tbreak\n73\t\t\t\t}\n74\t\t\t}\n75\t\t\tif !eq {\n76\t\t\t\tcontinue\n77\t\t\t}\n78\t\t\tif (i == 0 || !unicode.IsLetter(hay[i-1])) && (i+n == len(hay) || !unicode.IsLetter(hay[i+n])) {\n79\t\t\t\treturn true\n80\t\t\t}\n81\t\t}\n82\t\treturn false\n83\t}\n84\t\n85\t// windowMatch — совпадает ли окно outWords[i:i+n] с базовыми словами bw под правилом m.\n86\tfunc windowMatch(s lang.TargetStemmer, outWords, bw []string, i int, m mode) bool {\n87\t\tn := len(bw)\n88\t\tanyExact, anyNorm := false, false\n89\t\tnorm := make([]bool, n)\n90\t\tsoft := make([]bool, n)\n91\t\tfor k := 0; k < n; k++ {\n92\t\t\tow, bwk := outWords[i+k], strings.ToLower(bw[k])\n93\t\t\tif ow == bwk {\n94\t\t\t\tanyExact = true\n95\t\t\t}\n96\t\t\tnorm[k] = s.SameStem(ow, bw[k])\n97\t\t\tsoft[k] = softSameStem(s, ow, bw[k])\n98\t\t\tif norm[k] {\n99\t\t\t\tanyNorm = true\n100\t\t\t}\n101\t\t}\n102\t\tfor k := 0; k < n; k++ {\n103\t\t\tswitch m {\n104\t\t\tcase modeA0:\n105\t\t\t\tif !norm[k] {\n106\t\t\t\t\treturn false\n107\t\t\t\t}\n108\t\t\tcase modeA1:\n109\t\t\t\tif !soft[k] {\n110\t\t\t\t\treturn false\n111\t\t\t\t}\n112\t\t\tcase modeA2:\n113\t\t\t\tif !(norm[k] || (soft[k] && anyExact)) {\n114\t\t\t\t\treturn false\n115\t\t\t\t}\n116\t\t\tcase modeA3:\n117\t\t\t\tif !(norm[k] || (soft[k] && anyNorm)) {\n118\t\t\t\t\treturn false\n119\t\t\t\t}\n120\t\t\t}\n121\t\t}\n122\t\treturn true\n123\t}\n124\t\n125\tfunc countWindows(s lang.TargetStemmer, outWords, bw []string, m mode) int {\n126\t\tn := len(bw)\n127\t\tif n == 0 || n > len(outWords) {\n128\t\t\treturn 0\n129\t\t}\n130\t\tc := 0\n131\t\tfor i := 0; i+n <= len(outWords); i++ {\n132\t\t\tif windowMatch(s, outWords, bw, i, m) {\n133\t\t\t\tc++\n134\t\t\t}\n135\t\t}\n136\t\treturn c\n137\t}\n138\t\n139\tfunc firstWindowText(s lang.TargetStemmer, outWords, bw []string, m mode) string {\n140\t\tn := len(bw)\n141\t\tfor i := 0; i+n <= len(outWords); i++ {\n142\t\t\tif windowMatch(s, outWords, bw, i, m) {\n143\t\t\t\treturn strings.Join(outWords[i:i+n], \" \")\n144\t\t\t}\n145\t\t}\n146\t\treturn \"\"\n147\t}\n148\t\n149\t// present — порт dstFormPresent: базовая цельнословная форма ИЛИ декл-окно под правилом m.\n150\tfunc present(s lang.TargetStemmer, noutRunes, baseRunes []rune, outWords, bw []string, m mode) bool {\n151\t\tif containsWholeWord(noutRunes, baseRunes) {\n152\t\t\treturn true\n153\t\t}\n154\t\treturn countWindows(s, outWords, bw, m) > 0\n155\t}\n156\t\n157\tfunc loadBankDst(path string) ([]string, error) {\n158\t\traw, err := os.ReadFile(path)\n159\t\tif err != nil {\n160\t\t\treturn nil, err\n161\t\t}\n162\t\tlines := strings.Split(string(raw), \"\\n\")\n163\t\tseen := map[string]bool{}\n164\t\tvar out []string\n165\t\tfor i, ln := range lines {\n166\t\t\tif i == 0 || strings.TrimSpace(ln) == \"\" {\n167\t\t\t\tcontinue\n168\t\t\t}\n169\t\t\tf := strings.Split(ln, \"\\t\")\n170\t\t\tif len(f) < 2 {\n171\t\t\t\tcontinue\n172\t\t\t}\n173\t\t\tdst := strings.TrimSpace(f[1])\n174\t\t\tif dst == \"\" || seen[dst] {\n175\t\t\t\tcontinue\n176\t\t\t}\n177\t\t\tseen[dst] = true\n178\t\t\tout = append(out, dst)\n179\t\t}\n180\t\treturn out, nil\n181\t}\n182\t\n183\tfunc main() {\n184\t\tvar (\n185\t\t\tbankP = flag.String(\"bank\", \"\", \"BANK-FULL.tsv (col2 = dst)\")\n186\t\t\toutP = flag.String(\"output\", \"\", \"боевой target-выход (txt)\")\n187\t\t\trepP = flag.String(\"report\", \"\", \"куда писать отчёт (durable ~/books/...)\")\n188\t\t\ttgt = flag.String(\"tgt\", \"ru\", \"целевой язык\")\n189\t\t)\n190\t\tflag.Parse()\n191\t\tif *bankP == \"\" || *outP == \"\" || *repP == \"\" {\n192\t\t\tfmt.Fprintln(os.Stderr, \"usage: softsign-decl -bank B -output O -report R [-tgt ru]\")\n193\t\t\tos.Exit(2)\n194\t\t}\n195\t\tdsts, err := loadBankDst(*bankP)\n196\t\tif err != nil {\n197\t\t\tfmt.Fprintln(os.Stderr, \"bank:\", err)\n198\t\t\tos.Exit(1)\n199\t\t}\n200\t\trawOut, err := os.ReadFile(*outP)\n201\t\tif err != nil {\n202\t\t\tfmt.Fprintln(os.Stderr, \"output:\", err)\n203\t\t\tos.Exit(1)\n204\t\t}\n205\t\ts := lang.NewTargetStemmer(lang.TargetChecksFor(*tgt))\n206\t\tif !s.Enabled() {\n207\t\t\tfmt.Fprintln(os.Stderr, \"stemmer inert for\", *tgt)\n208\t\t\tos.Exit(1)\n209\t\t}\n210\t\tnout := text.NormalizeTargetForm(string(rawOut))\n211\t\tnoutRunes := []rune(nout)\n212\t\toutWords := lang.TokenizeWords(nout)\n213\t\n214\t\tvar b strings.Builder\n215\t\tpf := func(f string, a ...any) { fmt.Fprintf(&b, f, a...) }\n216\t\tpf(\"SOFT-SIGN DECL PROBE — bank=%d dst, output=%d words, tgt=%s\\n\", len(dsts), len(outWords), *tgt)\n217\t\tpf(\"A0=live(no «ь») · A1=naive global «ь» · A2=anchor:exact · A3=anchor:norm\\n\")\n218\t\tpf(\"========================================================\\n\\n\")\n219\t\n220\t\ttype row struct {\n221\t\t\tdst string\n222\t\t\tnWords int\n223\t\t\tsoftWord, softStem string\n224\t\t\ta0Win, a1Win, a2Win, a3Win int\n225\t\t\ta0Base bool\n226\t\t\ta2New, a3New string\n227\t\t}\n228\t\tvar soft []row\n229\t\tfor _, dst := range dsts {\n230\t\t\tbase := text.NormalizeTargetForm(dst)\n231\t\t\tbw := lang.TokenizeWords(base)\n232\t\t\tvar sw, ss string\n233\t\t\tfor _, w := range bw {\n234\t\t\t\tr := []rune(w)\n235\t\t\t\tif len(r) >= 4 && r[len(r)-1] == 'ь' {\n236\t\t\t\t\tsw, ss = w, string(r[:len(r)-1])\n237\t\t\t\t\tbreak\n238\t\t\t\t}\n239\t\t\t}\n240\t\t\tif sw == \"\" {\n241\t\t\t\tcontinue\n242\t\t\t}\n243\t\t\tsoft = append(soft, row{\n244\t\t\t\tdst: dst, nWords: len(bw), softWord: sw, softStem: ss,\n245\t\t\t\ta0Win: countWindows(s, outWords, bw, modeA0),\n246\t\t\t\ta1Win: countWindows(s, outWords, bw, modeA1),\n247\t\t\t\ta2Win: countWindows(s, outWords, bw, modeA2),\n248\t\t\t\ta3Win: countWindows(s, outWords, bw, modeA3),\n249\t\t\t\ta0Base: containsWholeWord(noutRunes, []rune(base)),\n250\t\t\t\ta2New: firstWindowText(s, outWords, bw, modeA2),\n251\t\t\t\ta3New: firstWindowText(s, outWords, bw, modeA3),\n252\t\t\t})\n253\t\t}\n254\t\tsort.Slice(soft, func(i, j int) bool { return soft[i].a3Win-soft[i].a0Win > soft[j].a3Win-soft[j].a0Win })\n255\t\n256\t\tpf(\"M1/M2. SOFT-SIGN TERMS (%d of %d dst) — occurrence-level windows captured\\n\", len(soft), len(dsts))\n257\t\tpf(\"dst | words | soft→stem | nomBase? | A0 A1 A2 A3 | A3−A0 | A3 first-new\\n----\\n\")\n258\t\tvar gA3multi, gA3single, gA2 int\n259\t\tfor _, r := range soft {\n260\t\t\tg3 := r.a3Win - r.a0Win\n261\t\t\tgA2 += r.a2Win - r.a0Win\n262\t\t\tif r.nWords > 1 {\n263\t\t\t\tgA3multi += g3\n264\t\t\t} else {\n265\t\t\t\tgA3single += g3\n266\t\t\t}\n267\t\t\tnt := \"\"\n268\t\t\tif g3 > 0 {\n269\t\t\t\tnt = r.a3New\n270\t\t\t}\n271\t\t\tpf(\"%-30s | %d | %s→%s | nom=%v | A0=%d A1=%d A2=%d A3=%d | +%d | %s\\n\",\n272\t\t\t\tr.dst, r.nWords, r.softWord, r.softStem, r.a0Base, r.a0Win, r.a1Win, r.a2Win, r.a3Win, g3, nt)\n273\t\t}\n274\t\tpf(\"\\nGAP (occurrence windows over A0): A3 multi=%d single=%d | A2 total=%d\\n\", gA3multi, gA3single, gA2)\n275\t\n276\t\t// M3: presence flips over ALL dst (worst case: every term vs whole book)\n277\t\tpf(\"\\nM3. PRESENCE FLIPS over ALL %d dst (A0-miss → variant-present)\\n\", len(dsts))\n278\t\ttype flip struct{ dst, win string }\n279\t\tvar f1, f2, f3 []flip\n280\t\tfor _, dst := range dsts {\n281\t\t\tbase := text.NormalizeTargetForm(dst)\n282\t\t\tbr := []rune(base)\n283\t\t\tbw := lang.TokenizeWords(base)\n284\t\t\tif present(s, noutRunes, br, outWords, bw, modeA0) {\n285\t\t\t\tcontinue\n286\t\t\t}\n287\t\t\tif present(s, noutRunes, br, outWords, bw, modeA1) {\n288\t\t\t\tf1 = append(f1, flip{dst, firstWindowText(s, outWords, bw, modeA1)})\n289\t\t\t}\n290\t\t\tif present(s, noutRunes, br, outWords, bw, modeA2) {\n291\t\t\t\tf2 = append(f2, flip{dst, firstWindowText(s, outWords, bw, modeA2)})\n292\t\t\t}\n293\t\t\tif present(s, noutRunes, br, outWords, bw, modeA3) {\n294\t\t\t\tf3 = append(f3, flip{dst, firstWindowText(s, outWords, bw, modeA3)})\n295\t\t\t}\n296\t\t}\n297\t\tdump := func(name string, fs []flip) {\n298\t\t\tpf(\"%s new presences: %d\\n\", name, len(fs))\n299\t\t\tfor _, x := range fs {\n300\t\t\t\tpf(\" %s ⟶ [%s]\\n\", x.dst, x.win)\n301\t\t\t}\n302\t\t}\n303\t\tdump(\"A1 (naive «ь»)\", f1)\n304\t\tdump(\"A2 (anchor=exact)\", f2)\n305\t\tdump(\"A3 (anchor=norm)\", f3)\n306\t\tin := func(fs []flip, d string) bool {\n307\t\t\tfor _, x := range fs {\n308\t\t\t\tif x.dst == d {\n309\t\t\t\t\treturn true\n310\t\t\t\t}\n311\t\t\t}\n312\t\t\treturn false\n313\t\t}\n314\t\tpf(\"\\nA1-ONLY presences (removed by anchor gate A3) — collision-suspect set:\\n\")\n315\t\tnOnly := 0\n316\t\tfor _, x := range f1 {\n317\t\t\tif !in(f3, x.dst) {\n318\t\t\t\tpf(\" %s ⟶ [%s]\\n\", x.dst, x.win)\n319\t\t\t\tnOnly++\n320\t\t\t}\n321\t\t}\n322\t\tpf(\" (count=%d)\\n\", nOnly)\n323\t\n324\t\t// M4: confirmed collision class (book-independent) under global soft SameStem vs anchor gate\n325\t\tpf(\"\\nM4. CONFIRMED COLLISION CLASS (fix-pack §а) — global soft (A1) vs single-word anchor gate\\n\")\n326\t\tfor _, p := range [][2]string{{\"Синь\", \"синим\"}, {\"Линь\", \"линий\"}, {\"Тень\", \"теней\"}} {\n327\t\t\tpf(\" A1 softSameStem(%q,%q)=%v (stems %q/%q) | anchor gate: lone word, no anchor ⟶ never soft\\n\",\n328\t\t\t\tp[0], p[1], softSameStem(s, p[0], p[1]), stemAug(s, p[0]), stemAug(s, p[1]))\n329\t\t}\n330\t\n331\t\tif err := os.WriteFile(*repP, []byte(b.String()), 0o644); err != nil {\n332\t\t\tfmt.Fprintln(os.Stderr, \"write report:\", err)\n333\t\t\tos.Exit(1)\n334\t\t}\n335\t\tfmt.Print(b.String())\n336\t\tfmt.Fprintf(os.Stderr, \"\\nreport written: %s\\n\", *repP)\n337\t}\n338\t"}]},"uuid":"0f2b32dc-f01d-4b5f-9c4f-7b94a9e7b642","timestamp":"2026-08-01T15:19:04.967Z","sourceToolAssistantUUID":"89836c21-46de-4a6d-a2f6-238de1029b5b","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"2b661d20-beb2-4637-804e-f9c7cb856202","isSidechain":true,"promptId":"a8c573a5-ab53-4aa9-b96e-0cc4596f62d1","agentId":"ad972fd5e7bb2dd5a","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_013bPm9UUBwGoSuRbi11BfM9","type":"tool_result","content":"1\tpackage lang\n2\t\n3\timport (\n4\t\t\"sort\"\n5\t\t\"strings\"\n6\t\n7\t\t\"textmachine/backend/internal/text\"\n8\t)\n9\t\n10\t// stemmer.go: the conservative TARGET stemmer (bank-quality §3, primitive C). It strips one inflectional\n11\t// ending off a word to get its stem, so a decl-aware check accepts an oblique case («мечом») against its\n12\t// nominative («меч») WITHOUT the seed listing every form — the fix for the decl-142/142-null false-miss\n13\t// noise, and the backstop the checker omission-detector shares. The ALGORITHM is generic; the ending REGISTRY\n14\t// is target data (decl_suffix in data/target-<tgt>.txt), so a target with none gets an inert stemmer (exact\n15\t// match only). A FLAGGER aid, biased to ACCEPT declensions; it never gates.\n16\t\n17\t// minStemRunes is the shortest stem a suffix strip may leave. Below it a \"stem\" is too short to distinguish\n18\t// two words (стripping «а» off «дома» is fine → «дом»; stripping it off «яма» to «ям» is not worth trusting),\n19\t// so the ending is not stripped and the word stands whole. Conservative on the side of NOT conflating words.\n20\tconst minStemRunes = 3\n21\t\n22\t// TargetStemmer strips a registry ending off a word. The zero value is a valid inert stemmer (no endings →\n23\t// Stem is the identity → SameStem is exact equality), which is what a target with no decl_suffix data gets.\n24\ttype TargetStemmer struct {\n25\t\tsuffixes []string // registry endings, longest-first\n26\t}\n27\t\n28\t// NewTargetStemmer builds the stemmer from a target's decl_suffix registry. No registry → an inert stemmer.\n29\tfunc NewTargetStemmer(tc TargetChecks) TargetStemmer {\n30\t\tsfx := append([]string(nil), tc.List(\"decl_suffix\")...)\n31\t\t// Longest-first so Stem strips the most specific ending (е.g. «ому» before «у»); ties by bytes for a\n32\t\t// stable, deterministic order.\n33\t\tsort.SliceStable(sfx, func(i, j int) bool {\n34\t\t\tif a, b := len([]rune(sfx[i])), len([]rune(sfx[j])); a != b {\n35\t\t\t\treturn a > b\n36\t\t\t}\n37\t\t\treturn sfx[i] < sfx[j]\n38\t\t})\n39\t\treturn TargetStemmer{suffixes: sfx}\n40\t}\n41\t\n42\t// Enabled reports whether the stemmer carries any endings — false for a target with no decl_suffix data, so a\n43\t// consumer can skip the whole stem branch.\n44\tfunc (s TargetStemmer) Enabled() bool { return len(s.suffixes) > 0 }\n45\t\n46\t// Stem returns word with its longest registry ending removed, provided the remaining stem stays ≥\n47\t// minStemRunes; otherwise the word is returned unchanged. Case-insensitive (folded to lower), so a match is\n48\t// case-blind. An empty or all-short word returns folded-as-is.\n49\tfunc (s TargetStemmer) Stem(word string) string {\n50\t\tw := strings.ToLower(word)\n51\t\trs := []rune(w)\n52\t\tif len(rs) < minStemRunes {\n53\t\t\treturn w\n54\t\t}\n55\t\tfor _, suf := range s.suffixes {\n56\t\t\tsr := []rune(suf)\n57\t\t\tif len(rs)-len(sr) < minStemRunes {\n58\t\t\t\tcontinue // stripping this ending would leave too short a stem\n59\t\t\t}\n60\t\t\tif strings.HasSuffix(w, suf) {\n61\t\t\t\treturn string(rs[:len(rs)-len(sr)])\n62\t\t\t}\n63\t\t}\n64\t\treturn w\n65\t}\n66\t\n67\t// SameStem reports whether two words share a stem under this stemmer — the decl-aware equality a consumer\n68\t// uses to accept one form of a word against another. Two identical words trivially match; the value the\n69\t// stemmer adds is matching «мечом»/«меча»/«меч». Never true for an inert stemmer beyond exact equality.\n70\tfunc (s TargetStemmer) SameStem(a, b string) bool {\n71\t\tla, lb := strings.ToLower(a), strings.ToLower(b)\n72\t\tif la == lb {\n73\t\t\treturn true\n74\t\t}\n75\t\tif !s.Enabled() {\n76\t\t\treturn false\n77\t\t}\n78\t\treturn s.Stem(la) == s.Stem(lb)\n79\t}\n80\t\n81\t// TokenizeWords splits a target string into its whole words (maximal letter runs), lower-cased. Script-\n82\t// generic (any Unicode letter), so it needs no per-language branch. Used to match a declined multi-word term\n83\t// head against the output. It delegates to text.TokenizeLetters — the ONE tokenizer, shared with the target\n84\t// lexical checkers' TokenizeScript, so a stress-accented output word no longer splits mid-word here either.\n85\tfunc TokenizeWords(s string) []string { return text.TokenizeLetters(s) }\n86\t"}]},"uuid":"942e39ca-4960-4809-a87c-df4b21995f6d","timestamp":"2026-08-01T15:19:05.480Z","sourceToolAssistantUUID":"2b661d20-beb2-4637-804e-f9c7cb856202","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"c9c01798-9296-4f7f-be9f-db3e8911f102","isSidechain":true,"promptId":"a8c573a5-ab53-4aa9-b96e-0cc4596f62d1","agentId":"ad972fd5e7bb2dd5a","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_014T33pV3JaVZzMJW9nWZNxn","type":"tool_result","content":"1\tpackage membank\n2\t\n3\timport (\n4\t\t\"strings\"\n5\t\t\"unicode\"\n6\t\n7\t\t\"textmachine/backend/internal/lang\"\n8\t\t\"textmachine/backend/internal/text\"\n9\t)\n10\t\n11\t// mempostcheck.go: the post-check (registry E1/E2 / research/13 Q5) — the main, almost\n12\t// free detector of silent degradation. For every injected record whose SRC actually\n13\t// fired in THIS chunk, it asks: did an accepted DST form appear in the output? A miss\n14\t// catches BOTH failure modes — \"the model ignored the glossary\" (soft-following loses\n15\t// 17–36% of terms, 2310.05824) AND \"we injected the wrong dst and the model obeyed it\"\n16\t// (the owner's fear, 2510.00829). It is a post-CHECK, never a blind post-REPLACE (E2):\n17\t// forcing a dictionary form into an oblique Russian case breaks agreement (46% of\n18\t// constrained-model errors in en-cs are agreement, 2106.12398), so v1 only FLAGS.\n19\t//\n20\t// Decl-awareness is load-bearing (research/14 §2, quantified): a naive \\b-regexp on the\n21\t// base form gives 18–36% FALSE flags on a hard chunk — inflected forms rendered\n22\t// CORRECTLY (\"Вэйчжуане\", \"Бородатого Вана\", \"Дэна\", \"сюцая\") that the boundary regexp\n23\t// misses. So the check matches against the STORED decl forms (filled at term-commit),\n24\t// not the bare lemma. BUT stored-decl reliability is itself a function of decl\n25\t// COMPLETENESS — an OOV translit name whose forms were under-filled re-introduces the\n26\t// same false flags. That is why v1 keeps the post-check a FLAGGER (observable, in the\n27\t// retrieval-state), NOT a hard disposition gate, until the false-flag rate is MEASURED\n28\t// on real inflected Russian (E1 — memory_e1_test.go). A hard gate flips on only after\n29\t// the owner validates precision (mirrors the coverage gate's opt-in, D12 Q4).\n30\t//\n31\t// Sticky records are DELIBERATELY excluded: a sticky entry's src is NOT in this chunk\n32\t// (that is why scene-inertia carries it), so its dst is legitimately absent from the\n33\t// output — post-checking it would false-flag every pronominal chunk. Only records whose\n34\t// key exactly fired here are expected in the output.\n35\t\n36\t// PostcheckMiss is one flagged term: an injected record whose src fired but whose dst\n37\t// (any accepted form) is absent from the output.\n38\ttype PostcheckMiss struct {\n39\t\tSrc string `json:\"src\"`\n40\t\tDst string `json:\"dst\"`\n41\t\tDisp string `json:\"disp\"` // confirmed | ambiguous (A2: ambiguous injections force a post-check)\n42\t}\n43\t\n44\t// PostcheckResult separates the two kinds of miss BY TYPE rather than by the discipline of whoever calls\n45\t// the checker (pack-20 / D39.42 п.4). The rule itself is unchanged and load-bearing: only a CONFIRMED\n46\t// miss is a consistency failure. An AMBIGUOUS miss is an auto/draft candidate the model was ENTITLED to\n47\t// reject, and counting it would invert the contract — punishing a model that correctly refused an\n48\t// unverified suggestion while passing one that obeyed a wrong CONFIRMED injection (external-review major\n49\t// #1). What changes is that the rule is now impossible to get wrong at a call site: there is no combined\n50\t// slice to filter, so a caller cannot forget to. The Unverified misses are still carried, in full, as\n51\t// observability (A2's forced post-check) — they are simply not a count.\n52\ttype PostcheckResult struct {\n53\t\tConfirmed []PostcheckMiss\n54\t\tUnverified []PostcheckMiss\n55\t\t// Shown / Followed are the $0 observability channel of the unverified wire: how many unsigned rows\n56\t\t// were actually PUT IN FRONT of the model here, and how many of those it went along with. Without the\n57\t\t// denominator \"3 deviations\" is unreadable — 3 out of 3 is a channel nobody follows, 3 out of 90 is\n58\t\t// a model exercising the judgement the unverified section explicitly grants it.\n59\t\tShown int\n60\t\tFollowed int\n61\t}\n62\t\n63\t// ConfirmedCount is the actionable consistency-failure count — the ONLY number allowed to gate.\n64\tfunc (r PostcheckResult) ConfirmedCount() int { return len(r.Confirmed) }\n65\t\n66\t// All returns every miss, confirmed first, for the human-facing detail blob.\n67\tfunc (r PostcheckResult) All() []PostcheckMiss {\n68\t\tif len(r.Unverified) == 0 {\n69\t\t\treturn r.Confirmed\n70\t\t}\n71\t\tout := make([]PostcheckMiss, 0, len(r.Confirmed)+len(r.Unverified))\n72\t\treturn append(append(out, r.Confirmed...), r.Unverified...)\n73\t}\n74\t\n75\t// Empty reports whether nothing at all was missed.\n76\tfunc (r PostcheckResult) Empty() bool { return len(r.Confirmed) == 0 && len(r.Unverified) == 0 }\n77\t\n78\t// Postcheck runs the decl-aware check over the injected records against the model\n79\t// output. Pure and deterministic. Returns the misses split by trust (empty = all fired terms present),\n80\t// plus the shown/followed counters of the unverified channel.\n81\tfunc (b *Bank) Postcheck(injected []PickedEntry, output string) PostcheckResult {\n82\t\tnout := text.NormalizeTargetForm(output)\n83\t\tvar res PostcheckResult\n84\t\tnoutRunes := []rune(nout)\n85\t\toutWords := lang.TokenizeWords(nout) // once for the whole chunk; the §3 stem branch reuses it per term\n86\t\tfor _, p := range injected {\n87\t\t\tif !p.valid() { // a caller-built zero record carries no row — nothing to check (pack-16 tail)\n88\t\t\t\tcontinue\n89\t\t\t}\n90\t\t\tif p.Sticky { // sticky context is not expected in the output\n91\t\t\t\tcontinue\n92\t\t\t}\n93\t\t\tif strings.TrimSpace(p.entry.dst) == \"\" { // a ruby candidate with no dst yet — nothing to check\n94\t\t\t\tcontinue\n95\t\t\t}\n96\t\t\tpresent := dstFormPresent(p.entry, noutRunes, outWords, b.stemmer)\n97\t\t\tif p.Disp != Confirmed {\n98\t\t\t\tres.Shown++\n99\t\t\t\tif present {\n100\t\t\t\t\tres.Followed++\n101\t\t\t\t}\n102\t\t\t}\n103\t\t\tif present {\n104\t\t\t\tcontinue\n105\t\t\t}\n106\t\t\tm := PostcheckMiss{Src: p.entry.src, Dst: p.entry.dst, Disp: string(p.Disp)}\n107\t\t\tif p.Disp == Confirmed {\n108\t\t\t\tres.Confirmed = append(res.Confirmed, m)\n109\t\t\t} else {\n110\t\t\t\tres.Unverified = append(res.Unverified, m)\n111\t\t\t}\n112\t\t}\n113\t\treturn res\n114\t}\n115\t\n116\t// dstFormPresent reports whether any accepted dst form of the entry appears in the\n117\t// normalized output as a WHOLE WORD (bounded by non-letters or string edges), not a bare\n118\t// substring. The whole-word rule closes self-review #3: a DROPPED short translit name\n119\t// («Ван») must not be masked by an unrelated common word that merely contains its letters\n120\t// («караВАН», «диВАН», «ИВАН» — a different person). Decl-aware (the research/14\n121\t// requirement): the stored decl forms carry the inflections a boundary regexp would miss.\n122\t//\n123\t// The accepted set is the UNION of the base dst AND the stored decl forms (D24.4 — D24.3 is\n124\t// the max_tokens floor, a different fix; the union is the post-check verdict change):\n125\t// the base translation is itself an approved form, so it is ALWAYS checked — not only as a\n126\t// fallback when decl is empty. Checking it only on empty decl false-flagged 37/55\n127\t// acceptance-stage-A misses (nominative_gap): an approved dst present in the NOMINATIVE\n128\t// while `decl.forms` listed only oblique cases (方源→Фан Юань present in the output, decl\n129\t// carried only genitive/dative). Requiring the base form to be duplicated into decl is\n130\t// redundant input every future book would trip on.\n131\t//\n132\t// PRECISION/RECALL TRADEOFF, not a free win (adversarial review, pkg 5): enlarging the\n133\t// accepted set is monotonic — it can only turn misses into passes, never the reverse. On\n134\t// the measured stage-A data those removed misses are all FALSE positives on correctly\n135\t// rendered nominatives (precision up, the 37/55). The one way it can COST recall is narrow\n136\t// but real: an entry whose decl OMITS the nominative AND whose base dst is a common word\n137\t// that recurs elsewhere while the term itself was DROPPED for its firing occurrence\n138\t// (剑→меч dropped as «клинок», yet an unrelated «меч» sits elsewhere) — this bag-of-words\n139\t// presence check then passes and masks the drop. That class is rare on real data (translit\n140\t// names do not recur coincidentally) and TOLERABLE only while this stays a FLAGGER: a\n141\t// hard-gate promotion (postcheck_gate) MUST re-measure recall on common-noun terms, not\n142\t// assume it — the \"recall unaffected\" phrasing in the D24.4 rationale is imprecise here.\n143\t// The remaining inflection_gap (18/55: a plural rendered but only the singular seeded) is a\n144\t// SEED completeness fix (Polygon), not a code one. noutRunes is the normalized output\n145\t// pre-decomposed.\n146\tfunc dstFormPresent(e *entry, noutRunes []rune, outWords []string, stemmer lang.TargetStemmer) bool {\n147\t\tif base := text.NormalizeTargetForm(e.dst); base != \"\" {\n148\t\t\tif containsWholeWord(noutRunes, []rune(base)) {\n149\t\t\t\treturn true\n150\t\t\t}\n151\t\t\t// §3: accept an OBLIQUE case of the base when the seed listed no decl forms (the measured 142/142-null\n152\t\t\t// noise). A component-wise stem match — «горы Цинмао» for «гора Цинмао», «мечом» for «меч» — with no\n153\t\t\t// assumption about which word inflects. Inert for a target with no decl_suffix registry.\n154\t\t\tif declinedFormPresent(outWords, base, stemmer) {\n155\t\t\t\treturn true\n156\t\t\t}\n157\t\t}\n158\t\tfor _, f := range e.declForms {\n159\t\t\tif f != \"\" && containsWholeWord(noutRunes, []rune(f)) {\n160\t\t\t\treturn true\n161\t\t\t}\n162\t\t}\n163\t\treturn false\n164\t}\n165\t\n166\t// declinedFormPresent reports whether the base rendering appears in the tokenized output with each of its\n167\t// words possibly inflected — a window of outWords the same length as base's words where every component\n168\t// shares its stem. Conservative (needs the whole phrase present, in order) and inert without a stemmer.\n169\tfunc declinedFormPresent(outWords []string, base string, stemmer lang.TargetStemmer) bool {\n170\t\tif !stemmer.Enabled() {\n171\t\t\treturn false\n172\t\t}\n173\t\tbw := lang.TokenizeWords(base)\n174\t\tn := len(bw)\n175\t\tif n == 0 || n > len(outWords) {\n176\t\t\treturn false\n177\t\t}\n178\t\tfor i := 0; i+n <= len(outWords); i++ {\n179\t\t\tall := true\n180\t\t\tfor k := 0; k < n; k++ {\n181\t\t\t\tif !stemmer.SameStem(outWords[i+k], bw[k]) {\n182\t\t\t\t\tall = false\n183\t\t\t\t\tbreak\n184\t\t\t\t}\n185\t\t\t}\n186\t\t\tif all {\n187\t\t\t\treturn true\n188\t\t\t}\n189\t\t}\n190\t\treturn false\n191\t}\n192\t\n193\t// containsWholeWord reports whether form occurs in hay with a letter-boundary on both\n194\t// ends (the char before the match is not a letter or is the start; likewise after). Runs\n195\t// on runes so Cyrillic boundaries are correct. O(len(hay)·len(form)) — fine, the\n196\t// post-check runs once per chunk over a handful of short forms.\n197\tfunc containsWholeWord(hay, form []rune) bool {\n198\t\tn := len(form)\n199\t\tif n == 0 || n > len(hay) {\n200\t\t\treturn false\n201\t\t}\n202\t\tfor i := 0; i+n <= len(hay); i++ {\n203\t\t\tif !text.RunesEqual(hay[i:i+n], form) {\n204\t\t\t\tcontinue\n205\t\t\t}\n206\t\t\tif (i == 0 || !unicode.IsLetter(hay[i-1])) && (i+n == len(hay) || !unicode.IsLetter(hay[i+n])) {\n207\t\t\t\treturn true\n208\t\t\t}\n209\t\t}\n210\t\treturn false\n211\t}\n212\t\n213\t// SpoilerLeak is one rendering the spoiler window REJECTED for this chapter that appeared in the output\n214\t// anyway — the self-inflicted spoiler the windows exist to prevent (D21 п.3 / research/15 §2.2).\n215\ttype SpoilerLeak struct {\n216\t\tSrc string `json:\"src\"`\n217\t\tDst string `json:\"dst\"`\n218\t\t// Since/Until are the window that excluded the row, so the operator sees at a glance whether the\n219\t\t// leak is a premature reveal (before since_ch) or a stale one (after until_ch).\n220\t\tSinceCh int `json:\"since_ch\"`\n221\t\tUntilCh int `json:\"until_ch\"`\n222\t}\n223\t\n224\t// SpoilerLeaks checks the chunk's REJECTED records against the model output: the row's key fired here,\n225\t// the window said the chapter must not know this rendering yet, and the rendering is in the output all\n226\t// the same. It is the reveal half of D21 п.3, built on the machinery that already exists — the selection\n227\t// records its rejects, and dstFormPresent already answers \"is this rendering here\" decl-aware — so it\n228\t// needs no schema and no second matcher.\n229\t//\n230\t// SCOPE, ratified (D39.55): \"a leak on a FIRED key\". Two classes are therefore OUT, and out on purpose\n231\t// rather than by oversight:\n232\t//\n233\t// - a STICKY carry rejected by the window (Sticky==true). Its key did NOT fire in this chunk, so the\n234\t// model was not looking at the entity here; counting it would silently widen the ratified scope on\n235\t// the back of the pack-19 fix that put those carries into Rejected at all;\n236\t// - a SOURCE-ANCHORED reveal — an identity twist whose source surface never occurs (the text says\n237\t// \"the stranger\", not the name). Nothing fires, so nothing is rejected, so there is nothing to\n238\t// check. Closing that class needs a target-side index of post-reveal renderings, which is a\n239\t// different mechanism and not this pack's.\n240\t//\n241\t// Pure and deterministic (rejected order, which Select fixes). Observability only — never a disposition.\n242\tfunc (b *Bank) SpoilerLeaks(rejected []PickedEntry, output string) []SpoilerLeak {\n243\t\tnorm := text.NormalizeTargetForm(output)\n244\t\tnout := []rune(norm)\n245\t\toutWords := lang.TokenizeWords(norm)\n246\t\tvar out []SpoilerLeak\n247\t\tfor _, p := range rejected {\n248\t\t\tif !p.valid() || p.Sticky {\n249\t\t\t\tcontinue\n250\t\t\t}\n251\t\t\tif strings.TrimSpace(p.entry.dst) == \"\" {\n252\t\t\t\tcontinue // nothing to leak\n253\t\t\t}\n254\t\t\tif !dstFormPresent(p.entry, nout, outWords, b.stemmer) {\n255\t\t\t\tcontinue\n256\t\t\t}\n257\t\t\tout = append(out, SpoilerLeak{\n258\t\t\t\tSrc: p.entry.src, Dst: p.entry.dst,\n259\t\t\t\tSinceCh: p.entry.sinceCh, UntilCh: p.entry.untilCh,\n260\t\t\t})\n261\t\t}\n262\t\treturn out\n263\t}\n264\t"}]},"uuid":"8086f84f-582a-43ab-a814-b56787bea683","timestamp":"2026-08-01T15:19:06.097Z","sourceToolAssistantUUID":"c9c01798-9296-4f7f-be9f-db3e8911f102","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"b20d066b-f826-4000-86e1-28d1e5edc237","isSidechain":true,"promptId":"a8c573a5-ab53-4aa9-b96e-0cc4596f62d1","agentId":"ad972fd5e7bb2dd5a","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_011KFR8KuAxNKRqQ6qQn3F5K","type":"tool_result","content":"/home/ubuntu/projects/textmachine/backend/internal/text/enclosure.go\n/home/ubuntu/projects/textmachine/backend/internal/text/source.go\n/home/ubuntu/projects/textmachine/backend/internal/text/runes.go\n/home/ubuntu/projects/textmachine/backend/internal/text/enclosure_test.go\n/home/ubuntu/projects/textmachine/backend/internal/text/norm_test.go\n/home/ubuntu/projects/textmachine/backend/internal/text/tokenize_test.go\n/home/ubuntu/projects/textmachine/backend/internal/text/norm.go\n---SEEDING---\nminerseed_contract_test.go\nseeding.go\n---LANGPACKS---\n/home/ubuntu/projects/textmachine/backend/configs/langpacks\n/home/ubuntu/projects/textmachine/backend/internal/lang/langpack.go\n/home/ubuntu/projects/textmachine/backend/internal/lang/langpack_test.go\n/home/ubuntu/projects/textmachine/backend/internal/lang/data/target-ru.txt\n/home/ubuntu/projects/textmachine/backend/internal/miner/testdata/langpack-overlay-guzhenren\n---BANK---\n/home/ubuntu/books/gu-zhenren/coldrun-a/BANK-FULL.tsv","is_error":false}]},"uuid":"4d522d7b-b81d-4a4b-9a21-628a398aefe3","timestamp":"2026-08-01T15:19:20.186Z","sourceToolAssistantUUID":"b20d066b-f826-4000-86e1-28d1e5edc237","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"4d522d7b-b81d-4a4b-9a21-628a398aefe3","isSidechain":true,"agentId":"ad972fd5e7bb2dd5a","message":{"model":"claude-opus-4-8","id":"msg_011CdcFeRGEacuxWKZPZcUyj","type":"message","role":"assistant","content":[{"type":"text","text":"Let me read the text package internals, the ru registry, and the bank file."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":911,"cache_read_input_tokens":33388,"cache_creation":{"ephemeral_5m_input_tokens":911,"ephemeral_1h_input_tokens":0},"output_tokens":8,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011CdcFeQ4JP53siou1o3HcT","attributionAgent":"general-purpose","type":"assistant","uuid":"63186caa-88d0-400e-bdfc-9b2a27be08da","timestamp":"2026-08-01T15:19:22.009Z","effort":"xhigh","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"bb2f9421-fbbd-4af5-aa2d-6319f1037849","isSidechain":true,"promptId":"a8c573a5-ab53-4aa9-b96e-0cc4596f62d1","agentId":"ad972fd5e7bb2dd5a","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Ao14sUHmjhQyNYjVPWt67D","type":"tool_result","content":"1\tpackage text\n2\t\n3\timport (\n4\t\t\"strings\"\n5\t\t\"unicode\"\n6\t)\n7\t\n8\t// runes.go: the rune/word primitives shared by the matchers that run over already-normalized\n9\t// text — the memory bank's whole-word post-check, the miner's containment/prefix tests and the\n10\t// cheap style checkers' word scans. They are deliberately allocation-free and script-agnostic;\n11\t// script-specific policy stays in its subsystem.\n12\t\n13\t// RunesEqual reports whether two rune slices of the SAME LENGTH hold the same runes.\n14\t// PRECONDITION: len(a) <= len(b) — the loop ranges over a and indexes b, so a shorter b\n15\t// panics. Every caller slices both sides to one length before calling (a fixed-width window\n16\t// scan), which is why the check is not repeated here: it is a hot inner loop of the\n17\t// post-check and of the miner's O(n·m) containment scan.\n18\tfunc RunesEqual(a, b []rune) bool {\n19\t\tfor i := range a {\n20\t\t\tif a[i] != b[i] {\n21\t\t\t\treturn false\n22\t\t\t}\n23\t\t}\n24\t\treturn true\n25\t}\n26\t\n27\t// TokenizeScript lower-cases text and splits it into maximal runs of letters in the given script `ws`\n28\t// (a Unicode range), dropping everything else (spaces, punctuation, digits, other scripts). A COMBINING\n29\t// MARK (unicode.Mn) inside a run does NOT break it and is dropped from the token, so a stress-accented word\n30\t// «сло́во» (о + U+0301) tokenizes as ONE word «слово», not «сло»+«во» (a leaked stress accent no longer\n31\t// splits a target word — pack-21 #11). It is the word unit of the →target lexical checkers: they compare\n32\t// whole words against a word list, so a run that stops at any non-word-script rune is exactly the boundary\n33\t// those checks need. The word SCRIPT is the target's declared alphabet (data), so the tokenizer is target-\n34\t// general; the ё/е distinction the yofication check measures is preserved (ё is a Cyrillic letter).\n35\tfunc TokenizeScript(text string, ws *unicode.RangeTable) []string {\n36\t\treturn tokenizeWords(text, func(r rune) bool { return unicode.Is(ws, r) })\n37\t}\n38\t\n39\t// TokenizeLetters is the SCRIPT-AGNOSTIC sibling of TokenizeScript: maximal runs of any Unicode letter,\n40\t// lower-cased, with the same combining-mark handling. For a caller that matches words regardless of the\n41\t// target's alphabet and has no declared script to pass — the decl-aware bank post-check tokenizes a target\n42\t// term head against the output without needing (or knowing) the target's word script. lang.TokenizeWords\n43\t// wraps it, so `lang` (which MAY import `text`) keeps one tokenizer instead of a second copy of this loop.\n44\tfunc TokenizeLetters(text string) []string {\n45\t\treturn tokenizeWords(text, unicode.IsLetter)\n46\t}\n47\t\n48\t// tokenizeWords is the shared core of TokenizeScript/TokenizeLetters: lower-case, then emit maximal runs of\n49\t// runes the predicate accepts, dropping a combining mark that sits on an open run rather than breaking it.\n50\tfunc tokenizeWords(text string, isWord func(rune) bool) []string {\n51\t\tvar words []string\n52\t\tvar b strings.Builder\n53\t\tflush := func() {\n54\t\t\tif b.Len() > 0 {\n55\t\t\t\twords = append(words, b.String())\n56\t\t\t\tb.Reset()\n57\t\t\t}\n58\t\t}\n59\t\tfor _, r := range strings.ToLower(text) {\n60\t\t\tswitch {\n61\t\t\tcase isWord(r):\n62\t\t\t\tb.WriteRune(r)\n63\t\t\tcase b.Len() > 0 && unicode.Is(unicode.Mn, r):\n64\t\t\t\t// a combining mark sits ON the preceding word base: keep the run open and drop the mark.\n65\t\t\tdefault:\n66\t\t\t\tflush()\n67\t\t\t}\n68\t\t}\n69\t\tflush()\n70\t\treturn words\n71\t}\n72\t\n73\t// TokenizeCyrillic is the ru-default word tokenizer (script = unicode.Cyrillic). The target-general pipeline\n74\t// path tokenizes on the target's DECLARED word script (Checkers.tokenizeWords); this wrapper serves callers\n75\t// that are unconditionally Russian (unit tests, ad-hoc tooling).\n76\tfunc TokenizeCyrillic(text string) []string { return TokenizeScript(text, unicode.Cyrillic) }\n77\t\n78\t// DenseScript reports whether r is a \"dense\" writing-system rune — a CJK ideograph, kana or Hangul syllable\n79\t// that maps to roughly ONE model token per character, versus an alphabetic script (~⅓ token/char). It is the\n80\t// SINGLE home of the token-sizing script class that render.EstimateTokens, chunk.TokenClassCounts and the\n81\t// memory-bank glossary budget all read, so the sizing taxonomy can never byte-drift across the packages\n82\t// (D39.60 §3.3 C-1: the same class was inlined in five places).\n83\tfunc DenseScript(r rune) bool {\n84\t\treturn unicode.In(r, unicode.Han, unicode.Hiragana, unicode.Katakana, unicode.Hangul)\n85\t}\n86\t\n87\t// DenseSparseCounts splits s into (dense, sparse) rune counts for the token estimate: dense = DenseScript\n88\t// runes (~1 token each), sparse = other letters/digits/punctuation (~⅓ token each); whitespace folds into\n89\t// neighbours and counts as neither. The shared classifier behind the reservation-sizing estimate AND the\n90\t// glossary-line budget — one taxonomy, so the \"second copy of the arithmetic\" can never diverge from the first.\n91\tfunc DenseSparseCounts(s string) (dense, sparse int) {\n92\t\tfor _, r := range s {\n93\t\t\tswitch {\n94\t\t\tcase DenseScript(r):\n95\t\t\t\tdense++\n96\t\t\tcase unicode.IsSpace(r):\n97\t\t\tdefault:\n98\t\t\t\tsparse++\n99\t\t\t}\n100\t\t}\n101\t\treturn dense, sparse\n102\t}\n103\t"}]},"uuid":"8af5d655-fda1-406c-a5ea-59f981b09923","timestamp":"2026-08-01T15:19:22.593Z","sourceToolAssistantUUID":"bb2f9421-fbbd-4af5-aa2d-6319f1037849","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"c1d29008-34e8-4016-90cb-038afd0137d4","isSidechain":true,"promptId":"a8c573a5-ab53-4aa9-b96e-0cc4596f62d1","agentId":"ad972fd5e7bb2dd5a","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01L2DKe8Fbx8hfUiqymcpNhA","type":"tool_result","content":"1\t// Package text is the pipeline's text substrate: the canonical forms a source or target string is\n2\t// reduced to before anything compares, matches or hashes it.\n3\t//\n4\t// It exists because three subsystems must agree on those forms EXACTLY — the memory bank matches and\n5\t// post-checks with them, the miner normalizes its candidate space with them, the cheap checkers tokenize\n6\t// with them — and a private copy in any of the three would be a silent match failure, not a compile\n7\t// error. Everything here is pure, deterministic and free of language policy: no pair data, no book\n8\t// canon, no configuration. The normalization ARTIFACT is versioned as a whole (NormVersion) and folded\n9\t// into the job snapshot, so changing a rule or the embedded trad→simp table is a loud --resnapshot\n10\t// rather than a quiet re-verdict on already-paid chunks.\n11\tpackage text\n12\t\n13\timport (\n14\t\t\"crypto/sha256\"\n15\t\t_ \"embed\"\n16\t\t\"encoding/hex\"\n17\t\t\"fmt\"\n18\t\t\"strings\"\n19\t\t\"unicode\"\n20\t\n21\t\t\"golang.org/x/text/unicode/norm\"\n22\t)\n23\t\n24\t// norm.go: the NORMALIZATION artifact behind every source/target match in the pipeline\n25\t// (registry A4 — the most likely \"silently empty\" bug: a glossary key is present in the\n26\t// chunk but in a different orthographic form, so the record silently fails to match).\n27\t// It is shared substrate: the memory bank matches and post-checks with it, the miner\n28\t// normalizes its candidate space with it, and the seed loader keys with it. Two pure,\n29\t// deterministic, VERSIONED normalizers, applied SYMMETRICALLY to both sides of every\n30\t// comparison:\n31\t//\n32\t// NormalizeSourceKey — zh/ja source surfaces (glossary keys/aliases AND chunk text):\n33\t// NFKC (fold half/full-width, e.g. ﾃ→テ, Ｑ→Q) → trad→simp (per-char, the\n34\t// embedded table) → katakana→hiragana fold → Unicode lower. So a key stored in\n35\t// Simplified still matches a Traditional source surface (魯鎮 ↔ 鲁镇), a full-width\n36\t// Ｑ matches a half-width Q, and スズキ matches すずき.\n37\t// NormalizeTargetForm — Russian dst forms (stored decl forms AND model output) for\n38\t// the post-check substring test: NFC → Unicode lower → ё→е fold.\n39\t//\n40\t// The whole artifact is versioned by NormVersion(), which is FOLDED INTO the\n41\t// snapshot via memoryVersion() (pipeline/snapshot.go): a change to the algorithm OR to the\n42\t// embedded trad→simp table is a loud --resnapshot, never a silent match-behaviour\n43\t// change on already-checkpointed chunks. Determinism is load-bearing — the injected\n44\t// glossary block is a pure function of (frozen glossary, normalized chunk), and it\n45\t// enters request_hash via the rendered messages.\n46\t\n47\t//go:embed data/trad2simp.txt\n48\tvar trad2simpRaw string\n49\t\n50\t// memoryNormAlgoVersion tags the normalization ALGORITHM (the pipeline of steps and\n51\t// their order). Bump it on an algorithm change. The trad→simp TABLE content is\n52\t// versioned SEPARATELY by hashing trad2simpRaw into memoryNormVersion below, so\n53\t// editing/completing the data file also invalidates — drift-proof (D8): you cannot\n54\t// forget to bump a version when you change the table, because the table's bytes ARE\n55\t// the version.\n56\t// Ш-2 (D39.16, folded here in R1): unicode.Version is woven into the algorithm tag so a Unicode-table\n57\t// bump (a go toolchain upgrade — NFKC/NFC via x/text, unicode.Is(Cf), the kana range, SignificantLen's\n58\t// unicode.Han/Cyrillic predicates) changes this version → the snapshot moves → a LOUD --resnapshot,\n59\t// never a silent match-behaviour change on already-checkpointed chunks. TRIPWIRE: do NOT bump the\n60\t// toolchain past the pinned Unicode edition without a --resnapshot (we are on go1.26.4 / Unicode 15.0.0).\n61\t//\n62\t// R1-FL-C: golang.org/x/text/norm carries its OWN Unicode edition INDEPENDENT of stdlib unicode.Version\n63\t// (its NFKC/NFC tables ship in the module, not the toolchain), so a standalone `go get -u golang.org/x/text`\n64\t// could silently shift NormalizeSourceKey's NFKC output → a re-verdict on the post-check WITHOUT moving the\n65\t// snapshot. Weaving xTextVersion in makes an x/text bump a loud --resnapshot too. It is a PINNED constant\n66\t// (debug.ReadBuildInfo returns an empty x/text version under `go test`, where the golden is captured, so a\n67\t// build-info fold would be non-deterministic) DRIFT-CHECKED against go.mod by TestMemnormXTextVersionPin:\n68\t// a go.mod bump that forgets this constant fails that test loudly — the tripwire enforced by mechanism.\n69\tconst xTextVersion = \"v0.38.0\" // MUST equal go.mod's golang.org/x/text (asserted by TestMemnormXTextVersionPin); a bump = --resnapshot\n70\tconst memoryNormAlgoVersion = \"memnorm-v3-nfkc+apos+stripignorable+trad+kana+lower/nfc+dash+apos+stripignorable+lower+yofold+u\" + unicode.Version + \"+xtext\" + xTextVersion\n71\t\n72\tvar (\n73\t\t// trad2simp is the parsed Traditional→Simplified single-char map (data/trad2simp.txt).\n74\t\ttrad2simp map[rune]rune\n75\t\t// memoryNormVersion is the snapshot-load-bearing version of the entire\n76\t\t// normalization artifact: the algorithm tag + a content hash of the embedded\n77\t\t// trad→simp table. memoryVersion() (pipeline/snapshot.go) folds it into the job snapshot.\n78\t\tmemoryNormVersion string\n79\t)\n80\t\n81\tfunc init() {\n82\t\ttrad2simp = parseTradTable(trad2simpRaw)\n83\t\th := sha256.Sum256([]byte(memoryNormAlgoVersion + \"\\x00\" + trad2simpRaw))\n84\t\tmemoryNormVersion = memoryNormAlgoVersion + \"-\" + hex.EncodeToString(h[:])[:12]\n85\t}\n86\t\n87\t// NormVersion returns the version of the whole normalization artifact (algorithm tag +\n88\t// content hash of the embedded trad→simp table). It is a function, not an exported var,\n89\t// so no caller can reassign the value the job snapshot folds.\n90\tfunc NormVersion() string { return memoryNormVersion }\n91\t\n92\t// parseTradTable parses the embedded \"<trad> <simp>\" table. Comment ('#') and blank\n93\t// lines are ignored; a non-empty content line that is NOT exactly two\n94\t// single-rune whitespace-separated fields is a corrupt table → panic at init (a\n95\t// loud build/test failure, caught the moment any test in the package runs, rather\n96\t// than a silently truncated map that would re-open the A4 hole). The table is\n97\t// authored in-repo and asserted by memnorm_test.go, so a panic here means the data\n98\t// file was corrupted, not bad user input.\n99\tfunc parseTradTable(raw string) map[rune]rune {\n100\t\tm := make(map[rune]rune, 1024)\n101\t\tfor i, line := range strings.Split(raw, \"\\n\") {\n102\t\t\tline = strings.TrimSpace(line)\n103\t\t\tif line == \"\" || strings.HasPrefix(line, \"#\") {\n104\t\t\t\tcontinue\n105\t\t\t}\n106\t\t\tfields := strings.Fields(line)\n107\t\t\tif len(fields) != 2 {\n108\t\t\t\tpanic(fmt.Sprintf(\"text: trad2simp table line %d: want 2 fields, got %d (%q)\", i+1, len(fields), line))\n109\t\t\t}\n110\t\t\ttr := []rune(fields[0])\n111\t\t\tsi := []rune(fields[1])\n112\t\t\tif len(tr) != 1 || len(si) != 1 {\n113\t\t\t\tpanic(fmt.Sprintf(\"text: trad2simp table line %d: each side must be a single rune (%q → %q)\", i+1, fields[0], fields[1]))\n114\t\t\t}\n115\t\t\t// A later duplicate wins deterministically (the file may list a char under\n116\t\t\t// two families); assert the mapping is consistent to catch a typo where the\n117\t\t\t// same trad char is mapped to two different simp chars.\n118\t\t\tif prev, ok := m[tr[0]]; ok && prev != si[0] {\n119\t\t\t\tpanic(fmt.Sprintf(\"text: trad2simp table line %d: %q maps to both %q and %q\", i+1, fields[0], string(prev), fields[1]))\n120\t\t\t}\n121\t\t\tm[tr[0]] = si[0]\n122\t\t}\n123\t\treturn m\n124\t}\n125\t\n126\t// NormalizeSourceKey normalizes a zh/ja SOURCE surface (a glossary key/alias OR the\n127\t// chunk text) for exact matching. Pure and deterministic; the pipeline is\n128\t// NFKC → drop default-ignorables → trad→simp (per rune) → katakana→hiragana → Unicode\n129\t// lower. Applied to BOTH keys and text so orthographic variants match (A4). Dropping\n130\t// default-ignorable/format code points (zero-width space/joiner, BOM, variation\n131\t// selectors) closes the re-opened A4 hole where a key 渡邊 silently misses a chunk\n132\t// surface 渡<ZWSP>邊 (common in scraped/EPUB CJK). Kana folding mirrors the eval spec\n133\t// (memory_hotpath.py): full-width katakana U+30A1..U+30F6 shift down 0x60 to hiragana;\n134\t// the prolonged-sound mark ー (U+30FC) and half-width forms are already handled (the\n135\t// latter by NFKC).\n136\tfunc NormalizeSourceKey(s string) string {\n137\t\ts = norm.NFKC.String(s)\n138\t\tvar b strings.Builder\n139\t\tb.Grow(len(s))\n140\t\tfor _, r := range s {\n141\t\t\tif isApostropheVariant(r) {\n142\t\t\t\tr = '\\'' // typographic apostrophe (O’Brien) folds to ASCII so a key matches either form\n143\t\t\t}\n144\t\t\tif isIgnorableForMatch(r) {\n145\t\t\t\tcontinue // zero-width / format / variation selector: invisible, never part of the key\n146\t\t\t}\n147\t\t\tif m, ok := trad2simp[r]; ok {\n148\t\t\t\tr = m\n149\t\t\t}\n150\t\t\tif r >= 0x30A1 && r <= 0x30F6 { // katakana → hiragana\n151\t\t\t\tr -= 0x60\n152\t\t\t}\n153\t\t\tb.WriteRune(unicode.ToLower(r))\n154\t\t}\n155\t\treturn b.String()\n156\t}\n157\t\n158\t// NormalizeTargetForm normalizes a Russian TARGET form (a stored decl form OR the\n159\t// model output) for the post-check whole-word test. Applied SYMMETRICALLY to both\n160\t// sides so a correctly-rendered term is NEVER a false MISS (over-flagging is the\n161\t// failure mode research/14 §2 warns about). Steps, each closing a self-review finding:\n162\t// - NFC;\n163\t// - dash/hyphen variants (en-dash, NB-hyphen, minus, soft hyphen, …) → ASCII '-', so\n164\t// «А–кью»/«А‑кью» match a stored «А-кью» (self-review #8);\n165\t// - drop default-ignorable/format code points (zero-width space/joiner, word joiner,\n166\t// BOM, variation selectors) that survive NFC, so a stored «вана» is not a false MISS\n167\t// against model output «ва<WJ>на» (over-flag; the soft hyphen is folded above, kept);\n168\t// - runs of ANY Unicode whitespace (newline, NBSP U+00A0, ideographic space, …) →\n169\t// one ASCII space, then trim, so a multi-word name wrapped across a line break\n170\t// («Бородатого\\nВана») matches a stored «Бородатого Вана» (self-review #2);\n171\t// - Unicode lower + ё→е fold (the ё-ification е/ё variation).\n172\t//\n173\t// Pure and deterministic.\n174\tfunc NormalizeTargetForm(s string) string {\n175\t\ts = norm.NFC.String(s)\n176\t\tvar b strings.Builder\n177\t\tb.Grow(len(s))\n178\t\tprevSpace := false\n179\t\tfor _, r := range s {\n180\t\t\tif isDashVariant(r) {\n181\t\t\t\tr = '-'\n182\t\t\t}\n183\t\t\tif isApostropheVariant(r) {\n184\t\t\t\tr = '\\'' // symmetric with the source side (д’Артаньян) — no false post-check MISS on a typographic apostrophe\n185\t\t\t}\n186\t\t\tif isIgnorableForMatch(r) {\n187\t\t\t\tcontinue // drop zero-width/format/VS (soft hyphen already folded to '-' above)\n188\t\t\t}\n189\t\t\tif unicode.IsSpace(r) {\n190\t\t\t\tif !prevSpace {\n191\t\t\t\t\tb.WriteByte(' ')\n192\t\t\t\t\tprevSpace = true\n193\t\t\t\t}\n194\t\t\t\tcontinue\n195\t\t\t}\n196\t\t\tprevSpace = false\n197\t\t\tr = unicode.ToLower(r)\n198\t\t\tif r == 'ё' {\n199\t\t\t\tr = 'е'\n200\t\t\t}\n201\t\t\tb.WriteRune(r)\n202\t\t}\n203\t\treturn strings.TrimSpace(b.String())\n204\t}\n205\t\n206\t// isDashVariant reports whether r is a hyphen/dash/minus variant that should fold to\n207\t// ASCII '-' for the post-check (Unicode dash punctuation + the math minus + soft hyphen).\n208\tfunc isDashVariant(r rune) bool {\n209\t\tswitch r {\n210\t\tcase '‐', '‑', '‒', '–', '—', '―', '−', '':\n211\t\t\treturn true\n212\t\t}\n213\t\treturn false\n214\t}\n215\t\n216\t// isApostropheVariant reports whether r is a typographic apostrophe/single-quote variant that\n217\t// should fold to ASCII '\\” (Task-6 re-audit): U+2018/U+2019 curly single quotes, U+02BC\n218\t// modifier-letter apostrophe, U+FF07 fullwidth apostrophe. Smart-quote editors turn a source\n219\t// key O'Brien's apostrophe into U+2019, which NFKC/NFC do NOT fold to U+0027 — leaving the key\n220\t// silently un-matchable (silently empty) on en names. Folded symmetrically on both sides.\n221\tfunc isApostropheVariant(r rune) bool {\n222\t\tswitch r {\n223\t\tcase '‘', '’', 'ʼ', '＇':\n224\t\t\treturn true\n225\t\t}\n226\t\treturn false\n227\t}\n228\t\n229\t// isIgnorableForMatch reports whether r is a default-ignorable / format code point that\n230\t// must be DROPPED before matching. These survive NFKC/NFC unchanged yet are invisible or\n231\t// carry no character identity, so leaving them in silently breaks a match — on the source\n232\t// side the A4 \"silently empty\" hole (a key 渡邊 misses 渡<ZWSP>邊), on the target side a false\n233\t// post-check MISS (a stored «вана» misses «ва<WJ>на»). Covers unicode.Cf (U+200B ZWSP,\n234\t// U+200C/D ZWNJ/ZWJ, U+2060 WJ, U+FEFF BOM, bidi marks, …) plus the variation selectors\n235\t// (VS1–16 U+FE00..FE0F and the ideographic supplement U+E0100..E01EF), which decorate a\n236\t// base glyph without changing it. The soft hyphen U+00AD is also unicode.Cf, but the\n237\t// target normalizer folds it to '-' via isDashVariant BEFORE consulting this predicate\n238\t// (self-review #8); on the source side (no dash semantics) dropping it is correct.\n239\tfunc isIgnorableForMatch(r rune) bool {\n240\t\tif unicode.Is(unicode.Cf, r) {\n241\t\t\treturn true\n242\t\t}\n243\t\treturn (r >= 0xFE00 && r <= 0xFE0F) || (r >= 0xE0100 && r <= 0xE01EF)\n244\t}\n245\t\n246\t// SignificantLen counts the \"significant\" characters of a normalized key — CJK\n247\t// ideographs/kana plus letters (Latin/Cyrillic) — for the single-key ban (registry\n248\t// A3): a key whose significant length is below minKeyLen may not fire on its own\n249\t// (a lone Han/kana/letter like 炎/气/钱 matches unrelated text on the wrong sense).\n250\t// Digits and punctuation do not count (so \"阿Q\" = 2, but a bare \"Q\" = 1). Mirrors the\n251\t// eval spec's cjk_len.\n252\tfunc SignificantLen(normalized string) int {\n253\t\tn := 0\n254\t\tfor _, r := range normalized {\n255\t\t\tswitch {\n256\t\t\tcase DenseScript(r):\n257\t\t\t\tn++\n258\t\t\tcase unicode.IsLetter(r):\n259\t\t\t\tn++\n260\t\t\t}\n261\t\t}\n262\t\treturn n\n263\t}\n264\t"}]},"uuid":"6ed53375-97f4-426c-bc46-985495f9b1c0","timestamp":"2026-08-01T15:19:23.567Z","sourceToolAssistantUUID":"c1d29008-34e8-4016-90cb-038afd0137d4","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"e4bdbac8-79ee-4c25-99e5-e12524054531","isSidechain":true,"promptId":"a8c573a5-ab53-4aa9-b96e-0cc4596f62d1","agentId":"ad972fd5e7bb2dd5a","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01QVLrQysRMjHsLz7V8Goj7P","type":"tool_result","content":"1\t# Target-language (ru) readability checker DATA (pair-14 data-out): the wordlists and DETECTION patterns the\n2\t# TARGET-GENERAL checkers/sanitizer run on ANY →ru output (regardless of source pair). Engine/target data —\n3\t# a no-langpack →ru book (the ja→ru golden) still runs these — so it is embedded here, not a book pack; the\n4\t# checker/sanitizer ALGORITHMS stay generic Go. `category<TAB>value`; value VERBATIM (a regex or a literal);\n5\t# lines are grouped by category IN ORDER (order matters for the sanitizer preamble preview). Add a target =\n6\t# add data/target-<tgt>.txt to the go:embed manifest (the target registry DERIVES from the file name).\n7\t#\n8\t# word_script: the target's WORD ALPHABET — the Unicode letter script the lexical checkers tokenize words on\n9\t# (whole-word wordlist match, broken-word/yofikation scan, latin-residue detection). The engine resolves the\n10\t# NAME to a Unicode range; it never branches on a language. `cyrillic` is the range for ru (unicode.Cyrillic).\n11\tword_script\tcyrillic\n12\t#\n13\t# broken-word: a Russian word ending in this suffix is a mangled infinitive (no valid word ends in «-йть»).\n14\tbroken_suffix\tйть\n15\t# speech-verb attribution: the verbs that make a chevron-quoted line SPOKEN dialogue rather than a\n16\t# thought. The dialogue-dash MIXING rule counts a chevron line only when its attribution carries one of\n17\t# these, i.e. the DEFAULT for an unrecognised attribution is \"not a style clash\" — precision over recall,\n18\t# the gate's stated bias. The inverse list (thought verbs) was tried first and proved unbounded: a live\n19\t# 2-chapter run immediately produced «понимал» and «размышлял», which no enumeration of thought verbs\n20\t# would have covered, while the speech-verb side is small and closed. Lower-cased, substring match.\n21\tspeech_verb\tсказал\n22\tspeech_verb\tсказала\n23\tspeech_verb\tответил\n24\tspeech_verb\tответила\n25\tspeech_verb\tспросил\n26\tspeech_verb\tспросила\n27\tspeech_verb\tкрикнул\n28\tspeech_verb\tкрикнула\n29\tspeech_verb\tвоскликнул\n30\tspeech_verb\tвоскликнула\n31\tspeech_verb\tпрошептал\n32\tspeech_verb\tпрошептала\n33\tspeech_verb\tпробормотал\n34\tspeech_verb\tпробормотала\n35\tspeech_verb\tпроговорил\n36\tspeech_verb\tпроговорила\n37\tspeech_verb\tпродолжил\n38\tspeech_verb\tпродолжила\n39\tspeech_verb\tдобавил\n40\tspeech_verb\tдобавила\n41\tspeech_verb\tвозразил\n42\tspeech_verb\tвозразила\n43\tspeech_verb\tпозвал\n44\tspeech_verb\tпозвала\n45\tspeech_verb\tобъявил\n46\tspeech_verb\tобъявила\n47\tspeech_verb\tпроизнёс\n48\tspeech_verb\tпроизнес\n49\tspeech_verb\tпроизнесла\n50\t# inner-speech VETO markers: a qualifier that makes a line inner speech even when its attribution verb\n51\t# is a speech verb — «пробормотал ПРО СЕБЯ» is a thought, not a spoken turn. Checked after speech_verb,\n52\t# so the pair (verb + veto) reproduces the writer's actual intent instead of the verb alone. Found by the\n53\t# 26.07 live verification: it was the single flag surviving on the real 10-chapter export.\n54\tinner_marker\tпро себя\n55\tinner_marker\tмысленно\n56\tinner_marker\tв мыслях\n57\tinner_marker\tсебе под нос\n58\tinner_marker\tв уме\n59\t# yofikator homograph whitelist: е-spellings that are DISTINCT words from their ё-counterpart (все≠всё,\n60\t# небо≠нёбо, берет≠берёт …), so the inconsistency rule must NOT flag «все»+«всё» as one word two ways.\n61\tyo_homograph\tвсе\n62\tyo_homograph\tвсех\n63\tyo_homograph\tвсем\n64\tyo_homograph\tвсеми\n65\tyo_homograph\tнебо\n66\tyo_homograph\tнебом\n67\tyo_homograph\tузнаем\n68\tyo_homograph\tузнаете\n69\tyo_homograph\tузнает\n70\tyo_homograph\tпадеж\n71\tyo_homograph\tпадежа\n72\tyo_homograph\tсовершенный\n73\tyo_homograph\tсовершенное\n74\tyo_homograph\tсовершенная\n75\tyo_homograph\tсовершенно\n76\tyo_homograph\tсовершенны\n77\tyo_homograph\tчем\n78\tyo_homograph\tтем\n79\tyo_homograph\tтема\n80\tyo_homograph\tтеме\n81\tyo_homograph\tтемы\n82\tyo_homograph\tберет\n83\tyo_homograph\tберете\n84\tyo_homograph\tберета\n85\tyo_homograph\tосел\n86\tyo_homograph\tосла\n87\tyo_homograph\tослы\n88\tyo_homograph\tослов\n89\tyo_homograph\tмел\n90\tyo_homograph\tмела\n91\tyo_homograph\tлен\n92\tyo_homograph\tлена\n93\tyo_homograph\tнес\n94\tyo_homograph\tнесем\n95\tyo_homograph\tнесет\n96\tyo_homograph\tвел\n97\tyo_homograph\tведет\n98\tyo_homograph\tведем\n99\t# magnitude_stem: Russian magnitude WORD stem → base-10 exponent, for the number-magnitude gate (a stem\n100\t# covers [base, base+2] since an unseen multiplier can lift it two orders). `magnitude_stem<TAB>stem<TAB>exp`.\n101\tmagnitude_stem\tтысяч\t3\n102\tmagnitude_stem\tмиллион\t6\n103\tmagnitude_stem\tмиллиард\t9\n104\tmagnitude_stem\tтриллион\t12\n105\t# sanitizer DETECTION patterns (pair-14 data-out). The sanitizer is isRuTarget-gated, so these are\n106\t# ru-target data; the strip/detect ALGORITHM stays in sanitizer.go. `sanitizer_preamble` is ORDERED\n107\t# (detectLeadingPreamble returns the FIRST match's preview). Values VERBATIM (regexes).\n108\tsanitizer_preamble\t(?is)^\\s*(?:вот|представляю|привожу|держите)\\s+[^\\n:]{0,40}?(?:отредактированн|исправленн|улучшенн)[а-яё]+\\s+(?:перевод|текст|вариант)[а-яё]*[^\\n:]{0,120}?:\n109\tsanitizer_preamble\t(?is)^\\s*(?:отредактированн|исправленн|улучшенн)[а-яё]+\\s+(?:перевод|текст|вариант)[а-яё]*[^\\n:]{0,120}?:\n110\tsanitizer_preamble\t(?is)^\\s*(?:вот\\s+)?перевод\\s+(?:фрагмента|текста|отрывка|главы|черновика)\\s*:\n111\tsanitizer_preamble\t(?is)^\\s*ниже\\s+(?:привед[её]н|представлен|дан|след)[а-яё]*\\s+[^\\n:]{0,40}?(?:перевод|отредактированн|текст)[а-яё]*[^\\n:]{0,20}?:\n112\tsanitizer_trailing_note\t(?i)^[*_>\\s-]{0,4}(?:(?:примечани[ея]|заметк[аи]|комментари[йяю]|пояснени[ея]|сноск[аи])\\s*:|(?:примечани[ея]|заметк[аи]|комментари[йяю])\\s+(?:переводчик|редактор)[а-яё]*|прим\\.\\s*(?:перев|ред)\\.?)\n113\tsanitizer_edit_meta\t(?im)^[*_>\\s-]{0,4}(?:(?:внесённ|внесен)[а-яё]+\\s+правк|основн[а-яё]+\\s+правк[а-яё]*(?:\\s+для\\s+справк[а-яё]+|\\s*:)|что\\s+(?:было\\s+)?(?:изменен|исправлен)|список\\s+(?:правок|изменений)|список\\s+внесённых)\n114\tsanitizer_invalid_sign\t(?i)(?:^|\\P{L})[ъь][а-яё]|[ъь][ъь]\n115\t# --- pack-19 voice flagger (T/V + attributed-reply checks) -----------------------------------------\n116\t# The T/V distinction is a fact about the TARGET language, so it lives here: a target that ships no\n117\t# tv_informal/tv_formal rows runs the whole voice flagger inert, with no Go edit. Surfaces are matched\n118\t# as WHOLE WORDS on the normalized output, lower-cased; only PRONOUNS and possessives are listed —\n119\t# verb agreement is morphology and belongs to the ru-target layer, not to a $0 flagger.\n120\ttv_informal\tты\n121\ttv_informal\tтебя\n122\ttv_informal\tтебе\n123\ttv_informal\tтобой\n124\ttv_informal\tтобою\n125\ttv_informal\tтвой\n126\ttv_informal\tтвоя\n127\ttv_informal\tтвоё\n128\ttv_informal\tтвое\n129\ttv_informal\tтвои\n130\ttv_informal\tтвоего\n131\ttv_informal\tтвоей\n132\ttv_informal\tтвоих\n133\ttv_informal\tтвоим\n134\ttv_informal\tтвою\n135\ttv_formal\tвы\n136\ttv_formal\tвас\n137\ttv_formal\tвам\n138\ttv_formal\tвами\n139\ttv_formal\tваш\n140\ttv_formal\tваша\n141\ttv_formal\tваше\n142\ttv_formal\tваши\n143\ttv_formal\tвашего\n144\ttv_formal\tвашей\n145\ttv_formal\tваших\n146\ttv_formal\tвашим\n147\ttv_formal\tвашу\n148\t# tv_plural_veto: Russian «вы» is ALSO plural-you, so a reply addressing several people legitimately\n149\t# mixes «ты» and «вы» («Ты иди, а вы оба ждите»). A reply carrying one of these markers is not counted\n150\t# as a T/V contradiction — the same veto shape inner_marker has over speech_verb, and for the same\n151\t# precision-over-recall reason: a miss here is silence on a real clash, not noise on good prose.\n152\ttv_plural_veto\tоба\n153\ttv_plural_veto\tобе\n154\ttv_plural_veto\tвдвоём\n155\ttv_plural_veto\tвтроём\n156\ttv_plural_veto\tвсе вы\n157\ttv_plural_veto\tвы все\n158\ttv_plural_veto\tгоспода\n159\ttv_plural_veto\tкаждый из вас\n160\t# self_ref_generic: the PLAIN first-person surfaces. They are the evidence that a character referred to\n161\t# herself at all — the check is «she said \"я\" where her profile says \"ваша служанка\"», i.e. the measured\n162\t# flattening class (research/15 §Пробы, marker 奴婢), never «she said \"я\"» on its own.\n163\tself_ref_generic\tя\n164\tself_ref_generic\tменя\n165\tself_ref_generic\tмне\n166\tself_ref_generic\tмной\n167\tself_ref_generic\tмною\n168\t# reply segmentation: how this target sets direct speech. reply_dash opens a dash-marked turn at line\n169\t# start; reply_open/reply_close bound a quoted turn. Data, not a Go literal, so a target with other\n170\t# conventions (ja 「」) states its own without touching the segmentation algorithm.\n171\treply_dash\t—\n172\treply_open\t«\n173\treply_close\t»\n174\t# translit-interjection blocklist (04-unhappy §9): JP/EN fillers that must be TRANSLATED/adapted, not\n175\t# transliterated into the target. Only surfaces that are NOT ordinary target words are listed (ара/уму were\n176\t# removed as high-FP collisions). The blocklist is TARGET data now (was a Go literal); the whole-word,\n177\t# case-insensitive matching ALGORITHM stays generic. D20.4: only the exact hyphenated reduplications listed\n178\t# fire — a generic «X-X» rule was rejected as too false-positive-prone. Extend per corpus finding.\n179\ttranslit_interjection\tара-ара\n180\ttranslit_interjection\tмаа\n181\ttranslit_interjection\tхмф\n182\ttranslit_interjection\tнани\n183\ttranslit_interjection\tауч\n184\ttranslit_interjection\tупс\n185\ttranslit_interjection\tкья\n186\ttranslit_interjection\tдесу\n187\t# decl_suffix: the productive Russian inflectional endings the decl-aware post-check stems a word by\n188\t# (bank-quality §3, primitive C). It lets dstFormPresent accept a term rendered in an oblique case\n189\t# («Фан Юаню» for «Фан Юань») WITHOUT the seed listing every form, closing the measured decl-142/142-null\n190\t# false-miss noise. TARGET data — the suffix set is ru-specific; the stemmer ALGORITHM (strip the longest\n191\t# listed ending that leaves a stem ≥ min length) stays generic Go and a target with no decl_suffix rows\n192\t# gets no stemming (inert). It is a FLAGGER aid, biased to ACCEPT declensions; it never gates. Ordered\n193\t# longest-first in code, so listing order here is free.\n194\tdecl_suffix\tами\n195\tdecl_suffix\tями\n196\tdecl_suffix\tого\n197\tdecl_suffix\tего\n198\tdecl_suffix\tому\n199\tdecl_suffix\tему\n200\tdecl_suffix\tыми\n201\tdecl_suffix\tими\n202\tdecl_suffix\tах\n203\tdecl_suffix\tях\n204\tdecl_suffix\tов\n205\tdecl_suffix\tев\n206\tdecl_suffix\tом\n207\tdecl_suffix\tём\n208\tdecl_suffix\tем\n209\tdecl_suffix\tой\n210\tdecl_suffix\tей\n211\tdecl_suffix\tый\n212\tdecl_suffix\tий\n213\tdecl_suffix\tая\n214\tdecl_suffix\tяя\n215\tdecl_suffix\tое\n216\tdecl_suffix\tее\n217\tdecl_suffix\tым\n218\tdecl_suffix\tим\n219\tdecl_suffix\tых\n220\tdecl_suffix\tих\n221\tdecl_suffix\tую\n222\tdecl_suffix\tюю\n223\tdecl_suffix\tа\n224\tdecl_suffix\tя\n225\tdecl_suffix\tу\n226\tdecl_suffix\tю\n227\tdecl_suffix\tе\n228\tdecl_suffix\tы\n229\tdecl_suffix\tи\n230\tdecl_suffix\tо\n231\t# NB (fix-pack §а, D39.71): the bare SOFT SIGN «ь» is deliberately NOT a decl_suffix. It would close the\n232\t# Palladius soft-sign case («Фан Юаню»~«Фан Юань» via the stem «юан»), but that strip is byte-identical in\n233\t# shape to a HARMFUL collision — «Синь»/«Линь» (top zh surnames) collapse onto «син»/«лин», the stems of the\n234\t# common words «синий»/«линия», which fires a spurious Bank.SpoilerLeaks false-positive (the noise direction).\n235\t# «юань»→«юан» and «синь»→«син» are the same 4-rune-soft-sign→3-rune-stem shape, so no min-stem rule separates\n236\t# them. The soft-sign nominative gap needs seed decl-form enumeration or an anchor-gated match, not this global\n237\t# suffix — see the fix-pack report §а ping.\n238\t"}]},"uuid":"f9def7d7-0bd2-4a60-b5fd-6999b209efcb","timestamp":"2026-08-01T15:19:23.636Z","sourceToolAssistantUUID":"e4bdbac8-79ee-4c25-99e5-e12524054531","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"ce453e31-ec5c-41c3-87fd-a03a47f03641","isSidechain":true,"promptId":"8e23d9c5-5128-407f-a60a-375398c62a45","agentId":"ad972fd5e7bb2dd5a","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_014UFVnWQr5Zv42CAnvw32Bx","type":"tool_result","content":"=== data lines (excl header):\n150\n=== uniq dst (col2) after trim:\n147\n=== empty dst count:\n0\n=== duplicate dst values (count>1):\n 2 ветвь Чи\n 2 талант класса Цзя\n 2 талант ранга Бин","is_error":false}]},"uuid":"268e0e78-0174-4d53-ae05-e857ef6383df","timestamp":"2026-08-01T15:21:50.594Z","sourceToolAssistantUUID":"ce453e31-ec5c-41c3-87fd-a03a47f03641","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"9ae2b5a4-9814-4156-84f6-0fb7ece32797","isSidechain":true,"promptId":"8e23d9c5-5128-407f-a60a-375398c62a45","agentId":"ad972fd5e7bb2dd5a","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01CuWNPkzpVb6PJETBGgCdav","type":"tool_result","content":"=== declForms references across backend ===\ninternal/membank/memory.go:147:\t// declForms are the normalized-target dst forms the post-check accepts. Empty →\ninternal/membank/memory.go:150:\tdeclForms []string\ninternal/membank/memory.go:315:\t\tif row.Decl != \"\" {\ninternal/membank/memory.go:321:\t\t\t\t\t\te.declForms = append(e.declForms, nf)\ninternal/store/glossary.go:18:// pipeline normalizes for matching (§3.6). Decl is a JSON blob the post-check reads.\ninternal/store/glossary.go:28:\tDecl string // JSON {\"invariant\":bool,\"forms\":[...]}\ninternal/seed/seed.go:70:\tDecl *Decl `yaml:\"decl\"`\ninternal/seed/seed.go:82:// Decl carries the target-side declension forms used by the post-check (an invariant\ninternal/seed/seed.go:84:type Decl struct {\ninternal/membank/memvoice.go:321:\t\t\tview.Forms = append([]string{base}, e.declForms...)\ninternal/checks/voice.go:371:// Forms carries the base dst plus its enumerated decl forms (the same decl.forms[] the bank uses). Stemming\ninternal/membank/mempostcheck.go:128:// while `decl.forms` listed only oblique cases (方源→Фан Юань present in the output, decl\ninternal/membank/mempostcheck.go:158:\tfor _, f := range e.declForms {\ninternal/membank/memseed.go:89:\t\tif t.Decl != nil {","is_error":false}]},"uuid":"4c679270-9d85-42f0-893b-7d9ff9c29a58","timestamp":"2026-08-01T15:21:59.757Z","sourceToolAssistantUUID":"9ae2b5a4-9814-4156-84f6-0fb7ece32797","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"826af8ec-43c2-45c2-8e5a-05379b2e52ef","isSidechain":true,"promptId":"8e23d9c5-5128-407f-a60a-375398c62a45","agentId":"ad972fd5e7bb2dd5a","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Uo8QYRaAtYCqKdDgYQaMqD","type":"tool_result","content":"60\t\n61\t// Term is one seeded term: the source surface, its rendering and the metadata the bank\n62\t// needs to inject it (gender/speech/declension, spoiler window, trust status, aliases).\n63\ttype Term struct {\n64\t\tSrc string `yaml:\"src\"`\n65\t\tDst string `yaml:\"dst\"`\n66\t\tType string `yaml:\"type\"`\n67\t\tSense string `yaml:\"sense\"`\n68\t\tGender string `yaml:\"gender\"`\n69\t\tSpeech string `yaml:\"speech\"`\n70\t\tDecl *Decl `yaml:\"decl\"`\n71\t\tTranslitPolicy string `yaml:\"translit_policy\"`\n72\t\tFirstPerson string `yaml:\"first_person\"`\n73\t\tNicknameTranslation string `yaml:\"nickname_translation\"`\n74\t\tSinceCh int `yaml:\"since_ch\"`\n75\t\tUntilCh int `yaml:\"until_ch\"`\n76\t\tStatus string `yaml:\"status\"`\n77\t\tAllowShort bool `yaml:\"allow_short\"`\n78\t\tNote string `yaml:\"note\"`\n79\t\tAliases []Alias `yaml:\"aliases\"`\n80\t}\n81\t\n82\t// Decl carries the target-side declension forms used by the post-check (an invariant\n83\t// term has none by design).\n84\ttype Decl struct {\n85\t\tInvariant bool `yaml:\"invariant\"`\n86\t\tForms []string `yaml:\"forms\"`\n87\t}\n88\t\n89\t// Alias is an additional source surface that fires for the same term.\n90\ttype Alias struct {\n91\t\tAlias string `yaml:\"alias\"`\n92\t\tType string `yaml:\"type\"`\n93\t}\n94\t"}]},"uuid":"d7ebd503-dcb2-450a-8fc1-559cd2c16e04","timestamp":"2026-08-01T15:22:04.228Z","sourceToolAssistantUUID":"826af8ec-43c2-45c2-8e5a-05379b2e52ef","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"d7ebd503-dcb2-450a-8fc1-559cd2c16e04","isSidechain":true,"agentId":"ad972fd5e7bb2dd5a","message":{"model":"claude-opus-4-8","id":"msg_011CdcFrDSfTSaukyPMZnZii","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_012K3mP5HYxHo6Tp1Lcnvy4d","name":"Read","input":{"file_path":"/home/ubuntu/projects/textmachine/backend/internal/membank/memseed.go","offset":75,"limit":30},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":986,"cache_read_input_tokens":60070,"output_tokens":240,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":986},"inference_geo":"not_available","iterations":[{"input_tokens":2,"output_tokens":240,"cache_read_input_tokens":60070,"cache_creation_input_tokens":986,"cache_creation":{"ephemeral_5m_input_tokens":986,"ephemeral_1h_input_tokens":0},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CdcFrATLKzZ9WCUdMmBZb","attributionAgent":"general-purpose","type":"assistant","uuid":"250594b4-8859-4ce6-90ea-d2d67c6a7e38","timestamp":"2026-08-01T15:22:04.720Z","effort":"xhigh","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"250594b4-8859-4ce6-90ea-d2d67c6a7e38","isSidechain":true,"promptId":"8e23d9c5-5128-407f-a60a-375398c62a45","agentId":"ad972fd5e7bb2dd5a","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_012K3mP5HYxHo6Tp1Lcnvy4d","type":"tool_result","content":"75\t\t\tswitch status {\n76\t\t\tcase \"auto\", \"draft\", \"approved\":\n77\t\t\tdefault:\n78\t\t\t\tproblems = append(problems, fmt.Sprintf(\"term %q: status must be auto|draft|approved, got %q\", t.Src, status))\n79\t\t\t\tcontinue\n80\t\t\t}\n81\t\t\t// An approved OR draft term with no dst is silently inert (not matchable — it renders\n82\t\t\t// nothing) yet reads as an intended rendering: fail loud (external-review minor #5).\n83\t\t\t// Only status=auto (a raw candidate — e.g. a ruby reading awaiting a dst) may be empty.\n84\t\t\tif (status == \"approved\" || status == \"draft\") && t.Dst == \"\" {\n85\t\t\t\tproblems = append(problems, fmt.Sprintf(\"term %q: a %s term must have a non-empty dst (an empty one is silently inert; only status=auto may lack a dst)\", t.Src, status))\n86\t\t\t\tcontinue\n87\t\t\t}\n88\t\t\tdecl := \"\"\n89\t\t\tif t.Decl != nil {\n90\t\t\t\tb, mErr := json.Marshal(declInfo{Invariant: t.Decl.Invariant, Forms: t.Decl.Forms})\n91\t\t\t\tif mErr != nil {\n92\t\t\t\t\treturn bs, mErr\n93\t\t\t\t}\n94\t\t\t\tdecl = string(b)\n95\t\t\t}\n96\t\t\te := store.GlossaryEntry{\n97\t\t\t\tBookID: \"\", Src: t.Src, Dst: t.Dst, Type: t.Type, Sense: t.Sense,\n98\t\t\t\tGender: t.Gender, Speech: t.Speech, Decl: decl,\n99\t\t\t\tTranslitPolicy: t.TranslitPolicy, FirstPerson: t.FirstPerson,\n100\t\t\t\tNicknameTranslation: t.NicknameTranslation,\n101\t\t\t\tSinceCh: t.SinceCh, UntilCh: t.UntilCh, Status: status,\n102\t\t\t\tAllowShort: t.AllowShort, Source: \"seed\", Note: t.Note,\n103\t\t\t}\n104\t\t\t// Dedup aliases within a term by surface (keep the first type). A repeated alias"}]},"uuid":"0449790b-0825-4f96-84ec-c0583016e7a9","timestamp":"2026-08-01T15:22:04.779Z","sourceToolAssistantUUID":"250594b4-8859-4ce6-90ea-d2d67c6a7e38","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"c9dc4896-d434-4a5b-a83b-c232d5279800","isSidechain":true,"agentId":"ad972fd5e7bb2dd5a","message":{"model":"claude-opus-4-8","id":"msg_011CdcFrZbNc1uvtcLz9Sxjf","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01RJRRZHyVPwz4vAN3dai2v9","name":"Bash","input":{"command":"cd /home/ubuntu/projects/textmachine/backend; echo \"=== miner decl emission? ===\"; grep -rn \"Decl\\|decl\\|Forms\\|forms\" internal/miner/*.go | grep -vi test | grep -i decl | head -20; echo \"=== any generator/enumerator of russian decl forms in Go? ===\"; grep -rln \"падеж\\|genitive\\|dative\\|inflect\\|enumerat\" internal --include=*.go | head; echo \"=== 142/142-null / nominative_gap origins ===\"; grep -rn \"142\\|nominative_gap\\|inflection_gap\" internal --include=*.go | grep -vi test | head","description":"Check miner decl emission and inflection generators"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1542,"cache_read_input_tokens":61056,"output_tokens":533,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":1542},"inference_geo":"not_available","iterations":[{"input_tokens":2,"output_tokens":533,"cache_read_input_tokens":61056,"cache_creation_input_tokens":1542,"cache_creation":{"ephemeral_5m_input_tokens":1542,"ephemeral_1h_input_tokens":0},"type":"message"}],"speed":"standard"},"diagnostics":{"cache_miss_reason":{"type":"unavailable"}}},"requestId":"req_011CdcFrY8oxVDzMsAiBJPuz","attributionAgent":"general-purpose","type":"assistant","uuid":"13c8c9fa-251b-41ac-b3bd-cdc44689d282","timestamp":"2026-08-01T15:22:14.889Z","effort":"xhigh","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"13c8c9fa-251b-41ac-b3bd-cdc44689d282","isSidechain":true,"promptId":"8e23d9c5-5128-407f-a60a-375398c62a45","agentId":"ad972fd5e7bb2dd5a","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01RJRRZHyVPwz4vAN3dai2v9","type":"tool_result","content":"=== miner decl emission? ===\ninternal/miner/miner_emit.go:52:\t// it is what selects the emission MODE in DeltaYAML (§C2-7). Empty when the role is off or declined the\ninternal/miner/miner_emit.go:60:// declined-term set (normalized src, R1-FL-B): a candidate whose entity touches a rejected surface is\ninternal/miner/miner_emit.go:61:// dropped from the delta so a declined term never re-fires the stop (a nil/empty rejects is a no-op — the\ninternal/miner/miner_emit.go:175:\t\t// A declined entity (R1-FL-B) is dropped WITH its whole cluster, so it never re-fires the stop:\ninternal/miner/miner_emit.go:327:// surfaces (an alias-of-existing entity) and the reject surfaces (a declined entity), which are treated the\n=== any generator/enumerator of russian decl forms in Go? ===\ninternal/checks/cheapgates_test.go\ninternal/pipeline/content_routing_test.go\ninternal/lang/stemmer.go\ninternal/membank/memdecl_test.go\ninternal/membank/memory.go\ninternal/miner/miner_detect.go\ninternal/checks/checkers_zh_ru_test.go\ninternal/pipeline/runner.go\ninternal/checks/voice.go\ninternal/terminology/terminology.go\n=== 142/142-null / nominative_gap origins ===\ninternal/lang/stemmer.go:12:// nominative («меч») WITHOUT the seed listing every form — the fix for the decl-142/142-null false-miss\ninternal/pipeline/banknote.go:279:// the probe's real blocks it was 142.6/147.2 est-tokens against a budget of 144: the reservation was at\ninternal/membank/mempostcheck.go:127:// acceptance-stage-A misses (nominative_gap): an approved dst present in the NOMINATIVE\ninternal/membank/mempostcheck.go:143:// The remaining inflection_gap (18/55: a plural rendered but only the singular seeded) is a\ninternal/membank/mempostcheck.go:151:\t\t// §3: accept an OBLIQUE case of the base when the seed listed no decl forms (the measured 142/142-null","is_error":false}]},"uuid":"f8f30954-26a7-485c-b55a-20b39f3ac841","timestamp":"2026-08-01T15:22:14.998Z","sourceToolAssistantUUID":"13c8c9fa-251b-41ac-b3bd-cdc44689d282","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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"}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1288,"cache_read_input_tokens":62598,"cache_creation":{"ephemeral_5m_input_tokens":1288,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011CdcFsHfh9QswmhhJP9u1J","attributionAgent":"general-purpose","type":"assistant","uuid":"44757bb4-5075-4ec4-bc31-aedf5bd7c7a1","timestamp":"2026-08-01T15:24:22.200Z","effort":"xhigh","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"44757bb4-5075-4ec4-bc31-aedf5bd7c7a1","isSidechain":true,"agentId":"ad972fd5e7bb2dd5a","message":{"model":"claude-opus-4-8","id":"msg_011CdcFsKkhkZuT3gKHLBuE7","type":"message","role":"assistant","content":[{"type":"text","text":"Let me verify the production bank builds its stemmer identically to the harness, and confirm `TargetChecksFor` wiring."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1288,"cache_read_input_tokens":62598,"cache_creation":{"ephemeral_5m_input_tokens":1288,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011CdcFsHfh9QswmhhJP9u1J","attributionAgent":"general-purpose","type":"assistant","uuid":"5c112f90-f5fb-427e-8dfa-2f61adcbba2f","timestamp":"2026-08-01T15:24:22.629Z","effort":"xhigh","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"5c112f90-f5fb-427e-8dfa-2f61adcbba2f","isSidechain":true,"agentId":"ad972fd5e7bb2dd5a","message":{"model":"claude-opus-4-8","id":"msg_011CdcFsKkhkZuT3gKHLBuE7","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01CaoyU15uAqcYE3PrdTzDt1","name":"Bash","input":{"command":"cd /home/ubuntu/projects/textmachine/backend; echo \"=== bank stemmer construction ===\"; grep -rn \"stemmer\\s*=\\|NewTargetStemmer\\|TargetChecksFor\\|stemmer:\" internal/membank/*.go internal/lang/*.go | grep -vi test | head; echo \"=== TargetChecksFor def ===\"; grep -rn \"func TargetChecksFor\\|func.*List(\" internal/lang/*.go | grep -vi test | head","description":"Confirm production stemmer construction parity"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":1288,"cache_read_input_tokens":62598,"cache_creation":{"ephemeral_5m_input_tokens":1288,"ephemeral_1h_input_tokens":0},"output_tokens":2,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011CdcFsHfh9QswmhhJP9u1J","attributionAgent":"general-purpose","type":"assistant","uuid":"ed68558b-c0cb-49dd-bf63-67c1224222cb","timestamp":"2026-08-01T15:24:25.188Z","effort":"xhigh","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"ed68558b-c0cb-49dd-bf63-67c1224222cb","isSidechain":true,"promptId":"8e23d9c5-5128-407f-a60a-375398c62a45","agentId":"ad972fd5e7bb2dd5a","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01CaoyU15uAqcYE3PrdTzDt1","type":"tool_result","content":"=== bank stemmer construction ===\ninternal/membank/memory.go:275:\tb := &Bank{keyOwners: map[string][]int{}, voices: in.Voices, pairs: in.Pairs, stemmer: in.TargetStemmer}\ninternal/lang/embedded.go:101:// TargetChecksFor returns the readability-checker data for a TARGET language, parsed once from the embedded\ninternal/lang/embedded.go:106:func TargetChecksFor(tgt string) TargetChecks {\ninternal/lang/stemmer.go:28:// NewTargetStemmer builds the stemmer from a target's decl_suffix registry. No registry → an inert stemmer.\ninternal/lang/stemmer.go:29:func NewTargetStemmer(tc TargetChecks) TargetStemmer {\n=== TargetChecksFor def ===\ninternal/lang/embedded.go:90:func (t TargetChecks) List(key string) []string { return t.byKey[key] }\ninternal/lang/embedded.go:106:func TargetChecksFor(tgt string) TargetChecks {","is_error":false}]},"uuid":"d90d313f-7436-4c32-8950-24258cfa2e30","timestamp":"2026-08-01T15:24:25.303Z","sourceToolAssistantUUID":"ed68558b-c0cb-49dd-bf63-67c1224222cb","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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{"parentUuid":"45f91061-a482-42cf-8faf-49e6714fad39","isSidechain":true,"agentId":"ad972fd5e7bb2dd5a","message":{"model":"claude-opus-4-8","id":"msg_011CdcG3H22ZzcSY7tSjnzue","type":"message","role":"assistant","content":[{"type":"text","text":"I have everything needed. Static analysis complete — no paid calls, `.env` untouched.\n\n---\n\n# ADVERSARIAL AUDIT — softsign-decl harness + recommendation\n\n## TARGET 1 — harness bug hunt\n\n**1. `stemAug` faithfulness (main.go:41-51) — NO-BUG.**\nChecked against \"add bare «ь» to the decl_suffix registry, longest-first, stem≥3.\" It is exactly faithful, provably:\n- Any word ending in «ь» is a **no-op under the real registry** — every registry suffix (target-ru.txt:194-230) ends in a vowel, so `HasSuffix(w,suf)` is false for all of them when `w` ends in ь. Hence `Stem(w)==w` and `stemAug` proceeds to strip ь. Registry+ь would do the same (ь is 1-rune, tried last, and is the only suffix that can match a ь-final word).\n- Any word **not** ending in ь never reaches the ь branch in either model; longest-first is preserved because ь can only win when nothing longer matches, and it never matches a non-ь-final word.\n- The `len(r)>=4` guard (main.go:47) is exactly `len(rs)-len(\"ь\") >= minStemRunes(3)` (stemmer.go:57). Boundary identical.\nNo input strips a different suffix than registry+ь would.\n\n**2. `windowMatch` anchor self-licensing (main.go:86-123) — NO-BUG.**\nA soft-only position **cannot** be its own anchor. If `norm[k]=false` then exact-at-k is necessarily false (exact equality ⟹ `SameStem` true ⟹ `norm[k]` true, stemmer.go:71-72; contrapositive). So a soft-only position contributes to **neither** `anyExact` **nor** `anyNorm` (both are OR-folds over `exact`/`norm` only, main.go:93-100). The licensing anchor is provably a **different** component. Corollary confirmed: a single-word term (`n=1`) can never be soft-licensed under A2/A3 — exactly what M4 asserts (\"lone word, no anchor ⟶ never soft\", main.go:327).\n\n**3. window bounds / A0 == `dstFormPresent` (main.go:125-155) — NO-BUG on logic; one intended scoping caveat.**\n`i+n <= len` loop bound is byte-identical to real `declinedFormPresent` (mempostcheck.go:178) and the `n==0 || n>len` guard matches (mempostcheck.go:175). A0 = base-whole-word OR stem-declined window = faithful port of `dstFormPresent` **minus** the `e.declForms` union (mempostcheck.go:158-162). That omission is deliberate and correct: the bank TSV carries no decl column, so the harness measures the **dst-only / 142-null** case by construction. Consequence to read correctly: harness A0 is a *lower bound* versus a production book with rich seeded declForms, but the load-bearing **A3−A0 / A2−A0 deltas are unaffected** (neither side has declForms). Not a bug.\n\n**4. `containsWholeWord` port (main.go:62-83) — NO-BUG.**\nThe inlined rune loop is semantically identical to `text.RunesEqual` + boundary test (mempostcheck.go:197-211): same `n==0||n>len(hay)` guard, same `hay[i+k]!=form[k]` comparison, same `!unicode.IsLetter` boundary on both edges. Inputs are equally normalized (`[]rune(NormalizeTargetForm(...))` on both sides).\n\n**5. `loadBankDst` (main.go:157-181) — NO-BUG. Verified against the real file.**\n`/home/ubuntu/books/gu-zhenren/coldrun-a/BANK-FULL.tsv`: 151 lines, header on line 0, **all 150 data rows have 8 tab fields, 0 blank lines**, col index 1 = `dst` (header `src\\tdst\\torigin\\ttype\\t…`). Exactly **3 duplicate dst** — «ветвь Чи», «талант класса Цзя», «талант ранга Бин» — so 150 − 3 = **147 uniq**, matching the harness's reported 147. Header-skip (`i==0`), tab-split, TrimSpace, dedup all correct. No drop/dup mis-parse.\n\n**6. tokenization / normalization / stemmer parity — NO-BUG.**\nHarness uses `text.NormalizeTargetForm` + `lang.TokenizeWords` for both base and output (main.go:210-212, 230-231) — identical to production `Postcheck` (mempostcheck.go:82-85) and `declinedFormPresent`. Stemmer is built via `lang.NewTargetStemmer(lang.TargetChecksFor(tgt))` — **byte-identical to production** (`pipeline/seeding.go:138`). Same registry data, same construction.\n\n**Extra finding (not in the hunt list) — soft is NOT a strict superset of norm; HARMLESS.**\nCounterexample: «конь»/«конья» — `SameStem` true (both stem to «конь»), but `softSameStem` false (`stemAug(\"конь\")=\"кон\"` vs `stemAug(\"конья\")=\"конь\"`). This does **not** corrupt any load-bearing number: A2/A3 evaluate `norm[k] || (soft[k]&&anchor)` (main.go:113,117), so `norm[k]` short-circuits first — a norm-match always passes. It touches only **A1** (the *rejected* rule, pure `soft[k]`, main.go:109), and can only *shrink* A1's captured set, never inflate it. So the \"A1-only / collision-suspect\" set (main.go:314-322) is at worst understated. This actually strengthens trust in A0/A2/A3.\n\n**Interpretation flag (not a bug):** M3 is a whole-book worst-case sweep of every dst — it drops the production `p.valid()/Sticky/Disp` filtering (mempostcheck.go:87-102). That is intentional and the code says so (main.go:276), but the M3 presence-flip counts should be read as an upper-bound worst case, not a per-chunk rate.\n\n## TARGET 2 — attack on the recommendation\n\n**Single strongest counter:** the recommendation is internally contradictory — it calls the false-miss \"not worth engine action\" while simultaneously prescribing **manual per-name seed decl-enumeration**, which is *not* zero action and is precisely the toil the §3 stemmer exists to abolish. Grounding:\n- `decl.forms` are **hand-authored YAML only** (`seed.go:84-87`, `Decl{Invariant, Forms []string}`). There is **no miner path** to Russian inflections — the miner's \"decl\" is *declined/rejected surfaces*, not morphology (`miner_emit.go:52-61`); no inflection generator exists anywhere in Go (grep confirms). So \"seed-enumerate\" = a human writes ~5-12 case forms per soft-final name, per book, forever.\n- The §3 stemmer's own charter is to KILL exactly this: *\"WITHOUT the seed listing every form\"* (stemmer.go:12), *\"Requiring the base form to be duplicated into decl is redundant input every future book would trip on\"* (mempostcheck.go:127-130). Recommendation #1 walks that back for the soft-final subclass and re-opens the same failure *direction* — an under-filled hand list = a silent false-flag, the 142/142-null noise it claims to close.\n- Generality check: seed `decl.forms` IS the architecturally-correct home for book-canon (engine Go must not branch on book; canon→seed data). So it doesn't break the invariant. But \"right data home\" ≠ \"not toil\": it's manual, per-book-recurring, and mineable-in-principle only by a morphology generator that doesn't exist — which is *why* the stemmer was built.\n\n**Steelman for building the engine anchor-match NOW:** the harness *measured* that A3 (anchor=norm) closes the **multi-word** soft gap while the single-word collision is provably neutralized (M4, `softSameStem(\"Синь\",\"синим\")=true` but lone→no anchor→never fires), and A3 ⊇ A0 so it can never mask a norm-match that A0 already caught. With a number-class stoplist + tail-restriction it's a *general, once-and-done* fix that every future book inherits free — versus per-name hand-toil that scales with the name inventory.\n\n**But — the caveat cuts BOTH ways (why the recommendation should CHANGE rather than either extreme win):** M4 tests only **3 hand-picked pairs** (Синь/Линь/Тень, main.go:326); the occurrence counts are one book. Per CLAUDE.md §4 and the vision memo, hand-picked / one-book empirics are **PRELIMINARY until a webnovel corpus slice**. So \"build the engine anchor-match now\" on that evidence would itself violate *validate-design-heuristics-on-corpus*: the [title]+[ь-surname] relocation collision and the number class the author flags are **unmeasured**, not disproven. The defensible resolution: (a) seed-enumerate ONLY the already-signed soft-final canon names as a cheap, exact, zero-collision **stopgap for this book** — that part is sound and bounded to the visible-name set; but (b) reframe \"defer to a 2nd book\" honestly as *\"gate the engine anchor-match on a corpus false-flag/false-negative count for the relocation + number classes,\"* not as if the recurring false-miss cost were zero.\n\n---\n\n## VERDICT\n**Harness numbers: TRUSTWORTHY.** The load-bearing A0/A2/A3 occurrence and presence figures are faithful ports on the byte-identical production stemmer; the only two divergences (declForms-union omission; soft⊉norm) are, respectively, the intended dst-only scope and inert to A0/A2/A3. loadBankDst's 147 is verified against the file.\n\n**Recommendation: SOUND in parts but should be SHARPENED.** Seed-enumeration of the handful of signed soft-final canon names is a fine bounded stopgap — but the recommendation must stop calling it \"zero action,\" acknowledge it resurrects the manual decl toil the §3 stemmer was built to kill (there is no miner for it), and replace \"defer to a 2nd book\" with an explicit corpus-measurement gate for the anchor-match's relocation and number-class risks, which the 3-pair M4 has not actually settled."}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":403,"cache_read_input_tokens":72582,"output_tokens":5839,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":403},"inference_geo":"not_available","iterations":[{"input_tokens":2,"output_tokens":5839,"cache_read_input_tokens":72582,"cache_creation_input_tokens":403,"cache_creation":{"ephemeral_5m_input_tokens":403,"ephemeral_1h_input_tokens":0},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CdcG3FU1xQThxkq5kvDW4","attributionAgent":"general-purpose","type":"assistant","uuid":"f5e556fb-8d36-4b21-b417-222b33b79d28","timestamp":"2026-08-01T15:25:57.094Z","effort":"xhigh","userType":"external","entrypoint":"claude-vscode","cwd":"/home/ubuntu/projects/textmachine","sessionId":"07c509cc-213b-44f5-ad8e-c3697b0c4bf7","version":"2.1.220","gitBranch":"main","slug":"nested-greeting-perlis"}
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