Claim the AI bounty on tDVV by delegating to the canonical repo SKILL and its branch docs; this public skill is AA/CA only and requires explicit write confirmation.
日本語の概要は準備中です。原文の説明を表示しています。
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概要と使いどころ
Claim the AI bounty on tDVV by delegating to the canonical repo SKILL and its branch docs; this public skill is AA/CA only and requires explicit write confirmation.
日本語の概要は準備中です。原文の説明を表示しています。
Triage a GitHub issue filed against skillsaw — classify it (bug, feature, docs, question, other), verify its claims against the codebase, enrich it with missing details, and post one structured triage comment. Use when triaging and labeling incoming issues, not to fix them.
日本語の概要は準備中です。原文の説明を表示しています。
Writing effective code documentation - API docs, README files, inline comments, and technical guides. Use for documenting codebases, APIs, or writing developer guides.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the primary outcome is authoring, rewriting, summarizing, or validating user-facing documentation without implementation comparison or required source attribution, including READMEs, tutorials, API docs, GitLab Markdown, source-faithful summaries, and audience-specific prose.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the primary outcome is comparing documentation claims with implementation evidence, synchronizing docs from verified changes, or freshness review, including drift, missing coverage, stale claims, and post-change updates.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user explicitly asks Rewrite Room to route documentation work, or when audit/sync/freshness, user-facing authoring, citation-driven writing, docs-to-skill conversion, and AI-instruction optimization overlap and exactly one workflow must be chosen.
日本語の概要は準備中です。原文の説明を表示しています。
Generates professional PyPI-compliant README files in Markdown or reStructuredText. Use when creating a Python package README for PyPI publication, converting between README.md and README.rst formats, validating markup with twine check before publishing, configuring the readme field in pyproject.toml, integrating sphinx-readme to generate PyPI-compatible RST from Sphinx docs, troubleshooting rendering errors on PyPI, or previewing README rendering locally with grip or docutils.
日本語の概要は準備中です。原文の説明を表示しています。
Sync a skill's content against the upstream library it covers — check whether the API descriptions, version references, and SOURCE: citations inside SKILL.md and its reference files still reflect what the library actually does today. Use when a library has released updates that may have changed the APIs the skill covers, when a skill references an old library version, when asked to sync, refresh, update, or check a skill against upstream docs, when the skill's content may have drifted from current library behavior, or when SOURCE: citations are stale. Accepts a SKILL.md path, skill directory, or plugin directory.
日本語の概要は準備中です。原文の説明を表示しています。
Cross-platform hooks reference for AI coding assistants — Claude Code, OpenAI Codex, GitHub Copilot, Cursor, Windsurf, and Amp. Covers hook authoring in Node.js (ESM and CJS) and Python, per-platform event schemas, inline-agent hooks and MCP in agent frontmatter, common JSON I/O, exit codes, best practices, and a fetch script to refresh docs from official sources. Use when writing, reviewing, or debugging hooks for any AI assistant.
日本語の概要は準備中です。原文の説明を表示しています。
Store instructional prose once and reference it from multiple skills or agents instead of duplicating it. Use when the same steps, rules, or reference material appear in two or more SKILL.md or agent files in one plugin, when deciding whether a shared doc belongs in the plugin-root docs directory or a single skill's references directory, or when tempted to use a symlink or a ../ path to share a file between components.
日本語の概要は準備中です。原文の説明を表示しています。
Plugin creator documentation index. Load when needing to read about plugin validation error codes, skill creation, agent creation, or plugin structure.
日本語の概要は準備中です。原文の説明を表示しています。
Add automated documentation updater to any Claude skill. Creates a Python sync script that downloads upstream docs, processes markdown for AI consumption, and maintains local cache with configurable refresh. Collects template variables, then delegates implementation through 5-phase workflow. Use when adding auto-updating reference documentation to plugins or skills.
日本語の概要は準備中です。原文の説明を表示しています。
Use when building, extending, or debugging FastMCP v4 (or v3) Python MCP servers. Activates on FastMCP tool/resource/prompt creation, provider and transform implementation (CodeMode, Tool Search), auth setup (MultiAuth, PropelAuth, KeycloakProvider), client SDK usage, FastMCPApp and Generative UI server building, fastmcp-slim client-only installs, nginx reverse proxy deployment, Prefab Apps, OTEL observability, testing, and v3→v4 migration. Grounded in official FastMCP v4 docs plus locally-verified v3 gotchas — zero speculation.
日本語の概要は準備中です。原文の説明を表示しています。
Entry point for refreshing the DH workflow graph. Use when skills, agents, Mermaid flowcharts, MCP tools, or artifact flows change and docs/dh-workflow-graph.json must remain current.
日本語の概要は準備中です。原文の説明を表示しています。
Orchestrator discipline plugin documentation index. Load when needing to read about orchestration patterns, delegation rules, or context window management.
日本語の概要は準備中です。原文の説明を表示しています。
Evaluate and iterate on the SDLC Layer Separation Architecture implementation. Runs validation checks (cross-references, doc completeness, layer metadata, integration points), produces a findings report, and supports iterative fixes. Use when validating first-pass implementation, before claiming layer work is complete, or when improving layer docs/schema.
日本語の概要は準備中です。原文の説明を表示しています。
Development harness plugin documentation index. Use when looking up SAM pipeline, backlog lifecycle, SDLC layers, task/plan schema, plan artifacts, quality gates, impact analysis, or dispatch schema documentation.
日本語の概要は準備中です。原文の説明を表示しています。
Builds comprehensive Claude Code skills using parallel research agents — categorization, parallel documentation gathering, anti-hallucination checkpoints, and final validation. Use when building a skill from official docs, when "research for skill" or "create comprehensive skill" is requested, or when extensive multi-source documentation gathering is needed before skill creation.
日本語の概要は準備中です。原文の説明を表示しています。
When writing a git commit message. When task completes and changes need committing. When project uses semantic-release, commitizen, git-cliff. When choosing between feat/fix/chore/docs types. When indicating breaking changes. When generating changelogs from commit history.
日本語の概要は準備中です。原文の説明を表示しています。
Validate and iterate on the SDLC Layer Separation Architecture implementation across the check categories defined in its Evaluation Checklist — cross-references, doc completeness, knowledge-explorer layer filters, research entry metadata, integration points, and plan consistency. Produces a structured findings report and optionally applies safe fixes. Use when validating a first-pass implementation, before claiming layer work complete, auditing layer docs or schema, or running --dry-run to preview findings without changes.
日本語の概要は準備中です。原文の説明を表示しています。
Agentskill kaizen plugin documentation index. Load when needing to read about cross-platform notes, improvement plans, or DuckDB integration.
日本語の概要は準備中です。原文の説明を表示しています。
This skill should be used when the user asks to "add an example", "write a tutorial", "document a new workflow example", or when creating a new worked example under `docs/source/examples/`.
日本語の概要は準備中です。原文の説明を表示しています。
Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user wants to create a new CLAUDE.md from scratch for a repository, bootstrap project memory for a new repo, set up a repo for Claude Code for the first time, or completely rewrite an existing CLAUDE.md deemed unsalvageable. Produces a lean, high-signal file under 80 lines (120 hard cap) by scanning the repo for mechanical content (stack, commands, structure) and interviewing the user for judgment content (WHY, gotchas, out-of-scope, approval gates, testing philosophy, external docs like Confluence pages). NOT for auditing or incrementally improving an existing CLAUDE.md — that is the claude-md-improver skill's role.
日本語の概要は準備中です。原文の説明を表示しています。