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概要と使いどころ
Use when the user names a coding or Claude Code task ("add OAuth", "set up hooks", "review this PR", "pick a model"), asks which prompt to use, says to "use the right prompt", or when you enter this repo and need to orient without reading every file.
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 before committing, opening a PR, or reporting a task done — when you want ground-truth confirmation there are no conflict markers, live-looking credentials, debug leftovers, untracked TODOs, or oversized files, without spending a model turn re-reading every file yourself.
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 cutting a release, writing a CHANGELOG entry, or summarizing what changed since a tag — when the repo's commits follow (or mostly follow) Conventional Commits and a mechanically-accurate section breakdown beats a model's reading of the diff.
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。
Run a bounded, report-only audit of coding-agent settings, instruction reachability, hooks, MCP wiring, and verification evidence with actionable findings.
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。
Orchestrate the repo workflow from brief through draft PR using skills and thin role wrappers.
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。
Review a branch or PR for merge readiness and produce a QA report.
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。
Uses htmltest to crawl generated documentation or static site output, detect broken internal and external links, and return a link-focused validation report before deploy. This is a narrow docs QA skill for agents validating already-built HTML, not a generic site generator or crawler listing.
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。
Extracts structured citation data from academic repositories using BeautifulSoup4 with lxml parser. Parses DOI metadata, author affiliations, and reference lists from PubMed, arXiv, and Semantic Scholar HTML.
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。
Score deep research agents on benchmark tasks using factual verification, report-quality scoring, and process evaluation before model or workflow changes ship.
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 MemoryBench to run repeatable conversational memory and RAG benchmarks across providers, datasets, judge models, checkpoints, and structured reports.
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。
Scan staged changes, commits, or repositories for secrets before they leave the workstation or CI job, instead of relying on a later platform-side catch.
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。
A fast, configurable secrets scanner built by the creator of Gitleaks and backed by Aikido Security. Betterleaks detects leaked passwords, API keys, and tokens in git repositories, directories, and stdin with CEL-based validation and parallelized scanning.
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 GEO SEO Claude when Claude Code should run repeatable AI-search and SEO audits with citability, crawler, schema, platform, and report workflows.
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 controlled retries to pytest runs so agents can contain flaky tests and report final failures without rerunning whole suites by hand.
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 REUSE when an agent needs file-level licensing clarity instead of guessing from a single top-level LICENSE file. The agent checks compliance, adds or verifies SPDX headers, pulls missing license texts into LICENSES/, and produces a concrete remediation list or SPDX export.
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。
Executes ansible-playbook --check --diff mode and parses the JSON callback output using the ansible.posix.json callback plugin. Identifies tasks that would change, predicts idempotency issues, and generates change impact reports.
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。
Aider is an open-source AI pair programming tool that runs in your terminal, letting you collaborate with LLMs to edit code across your entire codebase. With 42k+ GitHub stars and 15 billion tokens processed weekly, it features deep git integration, repo-wide code mapping, and support for 100+ programming languages.
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。
Decompose dense codebase-wide, multi-document, PDF, and aggregation work even when the input fits the context window, following Recursive Language Models (Zhang, Kraska, Khattab, 2025). Use when the user asks to analyse all files, a whole repo, all docs, large PDFs, or to aggregate or multi-hop across scattered sources. Skip one file, one function, a single needle, or a one-page PDF conversion. Triggers: long context, context rot, large codebase, many files, all files, big document, multi-document, PDF, aggregate, summarize everything, codebase-wide, multi-hop, recursive, sub-agents, map-reduce.
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。
CRISP Execute — Sprint execution loop with change request management, security gates, product gates, and stakeholder reporting. Use after Phase S (Spec) is complete and crisp-state.json shows ready_for_execute: true. Triggers on "start sprint", "begin build", "execute", "sprint 1", "run sprints", or when handed off from crisp-orchestrator.
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。
Consolidate the td-trend-scout reports under `_workspace/hype-scout/` into one prioritized HYPE_TOOL_BACKLOG.md — dedupe trends across surfaces, vet each candidate against the real tdmcp codebase (layer fit, operator coverage, bridge work), rank by Hype × Build-Ease, and emit a 'Ready for tdmcp-pipeline' top-5. Use when a td-hype-synthesizer agent is consolidating scouts at the end of the tdmcp-hype-scout harness.
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。
Study a merged or shipped tdmcp implementation and extract reusable learnings: code improvements, runtime/UX lessons, test gaps, docs updates, roadmap items, and harness changes. Use when the user asks to learn from a completed feature/project/PR/build, analyze what can be improved from an implementation, or turn a real installation experience into actionable tdmcp improvements. This is a post-implementation learning harness; it does not replace tdmcp-pipeline for building or tdmcp-quality-audit for broad repo audits.
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。
Consolidate the five tdmcp surveyor reports into one prioritized FEATURE_BACKLOG.md — dedupe cross-surface overlaps, reconcile every candidate against the roadmap (NEW vs planned vs extension), rank by a selectable impact×effort weighting profile into P0/P1/P2 (high-confidence first), and emit per-surface tables + a recommended-next shortlist that hands straight to the build pipeline. Use when a td-synthesizer agent is consolidating surveys during the feature-discovery harness.
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。
How to add a page to the tdmcp VitePress docs site so it builds, gets a clean URL, and lands in the right nav — including the repo's partial-translation convention (only the artist guide is EN+PT; reference/legal pages are English). Use when authoring the privacy policy or any new docs page for tdmcp.
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。
How to author one new tdmcp MCP tool the house way — the file shape (XImpl + registerX), the Python-bridge pattern (buildPayloadScript/parsePythonReport over executePythonScript), the result helpers (errorResult/guardTd/jsonResult/structuredResult), fail-forward error handling, ESM/.js + Biome style, and the offline msw unit test that proves it. Load this whenever building, extending, reviewing, or testing a tdmcp tool file under src/tools/** (and its test under tests/unit/**). Use it for every Phase-13 / v0.5.0 feature-build tool and any re-run after a gate failure.
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。