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Generates and updates project-facing documentation from the actual codebase — README, API reference, usage examples, and changelog entries — staying in sync with real code, signatures, and config. Use when docs are missing, stale, or after a feature/API change.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/Sir-chawakorn/sanook-cli --skill write-docs命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Gets machine-parseable JSON out of an LLM reliably — prefer provider-enforced grammar (OpenAI `response_format:{type:"json_schema",strict:true}`, Anthropic tool-calling / `tool_choice:{type:"tool"}`, Gemini `responseSchema`) over a "respond in JSON" prompt, define the contract once as a Pydantic/Zod model and validate every response (never trust the string), use constrained decoding / grammars for open weights (Outlines, llguidance, llama.cpp GBNF, vLLM `guided_json`), keep schemas SHALLOW with required fields + enums + `additionalProperties:false`, and build a repair-and-retry loop that handles refusals, `length`/`max_tokens` truncation, and streaming partial JSON (`partial-json-parser`). Schema-guided generation eliminates parse-error retries; validate-and-repair is the backstop, not the primary mechanism.
Builds production data grids that stay fast and accessible at 10k–1M+ rows — decide server-side vs client-side sort/filter/paginate by the dataset-fits-in-memory test (client only under ~10k rows, otherwise push to the API and treat the table as a controlled view of server state), ROW-VIRTUALIZE with TanStack Virtual or react-window so only the visible window mounts (fixed estimateSize, overscan 5–10, measureElement for dynamic rows, contain:strict, and a real scroll container — never table-layout:auto over thousands of rows), build the headless logic with TanStack Table v8 (or AG Grid when you need pinning/grouping/enterprise out of the box), add column resize/reorder/pin, inline edit with optimistic update + rollback on error, row selection with a stable rowId, full keyboard nav with roving tabindex over an ARIA grid (role=grid/row/gridcell, aria-sort, aria-rowcount/aria-rowindex so virtualization stays announced), position:sticky headers, streaming CSV export that doesn't block the main thread, and explici
Builds semantic/vector search — pick an embedding model + dimensionality (and whether to truncate Matryoshka dims) and the matching distance metric (cosine/dot/L2, normalize to unit length so cosine == dot and IP is correct), an ANN index with the recall/latency/memory tradeoff understood (HNSW M/efConstruction/efSearch for low-latency RAM-resident; IVF-PQ nlist/nprobe/PQ for billion-scale compressed; flat/exact for <100k) in pgvector/Qdrant/Milvus/FAISS/Pinecone, chunking + overlap + per-chunk metadata for filtering, HYBRID retrieval fusing BM25 + dense by Reciprocal Rank Fusion (RRF, k≈60) not score addition, a cross-encoder/Cohere reranker over the top-50→k, correct pre-filter-vs-ANN interaction (filterable HNSW, not post-filter that starves k), and offline eval with recall@k / nDCG@10 / MRR against a labeled qrels set. Quantize (scalar/PQ) only after measuring recall loss; tune efSearch/nprobe to a recall target, not a guess.
基于 SOC 职业分类
正在显示 SKILL.md
| name | write-docs |
| description | Generates and updates project-facing documentation from the actual codebase — README, API reference, usage examples, and changelog entries — staying in sync with real code, signatures, and config. Use when docs are missing, stale, or after a feature/API change. |
| when_to_use | README/docs ขาดหรือ stale; หลังเพิ่ม feature/เปลี่ยน API; ต้องสร้าง changelog/usage example |
Do NOT use for inline code comments or design docs — this skill produces user-facing docs only.
Scan real structure first — never write from memory.
package.json bin/main/exports, pyproject.toml [project.scripts], Cargo.toml [[bin]], or the file the README claims. Confirm it exists.package.json scripts, Makefile targets, declared CLI subcommands.index/__init__/lib.rs/public exports), not internal helpers.grep for process.env., os.environ, Deno.env), config-file schema, default values. Use the real defaults from code, not guesses.Generate/update README with sections, in this order:
npm i <name>, pip install <name>, etc.). Verify the package name from the manifest, don't assume the repo name.Key | Type | Default | Description, populated from code-confirmed values only.Write API reference from real signatures. For each public symbol, pull the actual signature (params, types, return, throws) from source/type definitions. Match parameter names and order exactly. If a param has a default in code, show that default. Omit private/underscored/unexported symbols.
Build changelog from commits. git log <last-tag>..HEAD --oneline. Parse Conventional Commits (feat:, fix:, perf:, refactor:, docs:, chore:...). Group under headings: Added (feat), Fixed (fix), Changed (refactor/perf), etc. Mark BREAKING CHANGE:/! commits prominently. Drop noise (merge commits, chore: bump, CI). Prepend a new version section above existing entries — never rewrite history.
Verify every example runs. Execute each quickstart/usage snippet (or --help for CLI flags) and confirm it succeeds. If a snippet can't be run in this environment, mark it clearly and base it strictly on a verified signature, not invention.
grep doesn't find it, it doesn't go in the docs./path/to/project, <your-api-key>, example.com).grep).