Count-based quantity takeoff and tag completeness auditing for construction drawings. Vision + OCR reconciliation, sheet markup, Excel QTO output. Triggers: 'tag audit', 'quantity takeoff', 'QTO', 'count fixtures'.
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
Count-based quantity takeoff and tag completeness auditing for construction drawings. Vision + OCR reconciliation, sheet markup, Excel QTO output. Triggers: 'tag audit', 'quantity takeoff', 'QTO', 'count fixtures'.
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。
Audit Claude Code session logs (~/.claude/projects) for token waste and produce a ranked, attributed efficiency report (habit / skill_file / config). Use when the user asks to audit session efficiency, analyze token waste or cost blowups, review Claude Code usage cost, or asks "where are my tokens going".
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。
Full website SEO audit with parallel subagent delegation. Crawls up to 500 pages, detects business type, delegates to 7 specialists, generates health score. Use when user says "audit", "full SEO check", "analyze my site", or "website health check".
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。
Burn Red Book audio CDs or MP3 data CDs on macOS via cdrdao, sourcing from Hoodrat HDD or local files. Audio CDs carry CD-Text from ID3 tags; MP3 discs use ISO9660+Joliet (~700 MB). Handles full-album burns and cherry-picked playlists. Triggers on 'burn CD', 'burn album', 'make audio CD', 'mixtape disc', 'soundtrack for the car'.
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。
Send, read, and respond to Telegram messages as Claudicle via the @claudicle_bot Bot API. Use this skill when sending Telegram messages (text, Markdown, inline keyboards), building approval gates with tappable buttons, checking the shared inbox for unhandled Telegram messages, answering callback queries, managing Telegram memory context, or checking bot and listener status. Five purpose-built scripts (send, check, status, callback, memory) wrap the python-telegram-bot v22 polling adapter at ~/.claudicle/adapters/telegram/ with REST-based senders (no asyncio). Pairs with /telegram-respond for the cognitive pipeline and with mazkir-callback-watcher.py for the Mazkir approval gate.
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。
Audit a repo's test, lint, type-check, static analysis, build, and debug infrastructure for AI coding agents. Generate scored reports and optimized configs for the lint-on-write hook. Triggers on audit tests, test harness, lint setup, check test infrastructure, entering a new repo.
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 technical quality checks across accessibility, performance, responsive design, theming, and anti-patterns. Generate a scored report with P0-P3 severity ratings. Report-only — documents issues for other skills to fix. Triggers on audit the design, check accessibility, technical review, performance audit, a11y check.
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 creating, auditing, or maintaining AGENTS.md files and Codex CLI configuration for any project—including initializing AGENTS.md for cross-agent compatibility (Codex, Cursor, Copilot, Devin, Jules, Amp, Gemini CLI), generating config.toml or .rules files, scaffolding .agents/skills/, converting CLAUDE.md to AGENTS.md, or auditing existing agent configs for bloat and staleness. Complementary to codex-orchestrator (which executes subagents; this skill creates the config files they consume).
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。
Implement audit trail functionality for R projects in regulated environments. Covers logging, provenance tracking, electronic signatures, data integrity checks, and 21 CFR Part 11 compliance. Use when an R analysis requires electronic records compliance (21 CFR Part 11), when you need to track who did what and when in an analysis, when implementing data provenance tracking, or when creating tamper-evident analysis logs for regulatory submissions.
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。
Set up systematic data labeling workflows using Label Studio or similar tools. Implement quality controls, measure inter-annotator agreement, manage labeler teams, and integrate labeled data into ML training pipelines. Use when starting a supervised ML project that requires labeled training data, when model performance is limited by insufficient labeled examples, when labeling text, images, audio, or video, or when implementing active learning to prioritize the most valuable 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。
Audit project dependencies for version staleness, security vulnerabilities, and compatibility issues. Covers lock file analysis, upgrade path planning, and breaking change assessment. Use before a release to ensure dependencies are current and secure, during periodic maintenance reviews, after receiving a security advisory, when upgrading to a new language version, before submitting to CRAN or npm, or when inheriting a project to assess its dependency health.
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。
Audit and repair Claude Code discovery symlinks for skills, agents, and teams. Compares registries against .claude/ directories at project and global levels, detects missing, broken, and extraneous symlinks, distinguishes almanac content from external projects, and optionally repairs gaps. Use after adding new skills or agents, after a repository rename or move, when slash commands stop working, or as a periodic health check.
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。
Read-only audit of a GitHub repository's security posture. Gathers ref protection (rulesets AND classic branch protection), Actions token permissions, code and supply-chain features (Dependabot, secret scanning, push protection, CodeQL), and repo hygiene toggles via `gh api`, then classifies findings against essential / recommended / advanced tiers into a PASS/GAP report. Makes NO changes. Use when reviewing a repo before open-sourcing or a release, auditing a public user-owned repo whose CI auto-commits to the default branch, verifying a hardening change actually took effect, or producing a baseline security posture report for a repository.
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 directing, building, or auditing React/Next.js Tailwind UI: visual direction, responsive/dark-mode retrofits, UX audits. Not for typography or motion: use typography-audit or ui-animation.
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 the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," or "SEO health check." For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema-markup.
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。
Launches 5 parallel AI agents to produce a comprehensive restaurant audit with composite Restaurant Health Score (0-100), grade, and prioritized action plan
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。
Audit a NowStack Mobile iOS app against the App Store Review Guidelines before submission - account deletion, IAP/Restore + no Stripe on iOS, Sign in with Apple parity, permission strings, App Privacy, AI disclosure, export compliance. Use for "ns ios audit" or "will my app pass App Store review".
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。
Programmatic React video best practices for Remotion. Use this skill whenever the user is writing, debugging, or rendering Remotion code — compositions, useCurrentFrame animations, interpolate, spring, Sequence timing, <Img>/<Video>/<Audio> from @remotion/media, staticFile, calculateMetadata, the Studio preview, `npx remotion render`, captions, subtitles, voiceover, audio visualization, ffmpeg, transitions, light leaks, transparent video, Lottie, 3D scenes, Mapbox flyovers. Triggers especially on HtmlInCanvas / "html in canvas" requests, CRT terminal effects, glitch effects, video shaders, WebGL video, and any request to scaffold a new programmatic React video. Owns `remotion render` and everything about Remotion code. Do NOT trigger for finished MP4 ad assembly from existing slides (that is `/video-content`) or for the inspiration-to-MP4 reference-video pipeline (that is `/cmo-video`).
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。
Audit web pages and components against RAWeb 1.1 (Luxembourg Web Accessibility Framework). Use when reviewing existing code for accessibility compliance, generating audit reports, checking conformance levels, or preparing for Luxembourg accessibility certification. Covers all 17 themes with systematic test procedures. Default target: Level AA.
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。
Audit mobile applications (iOS and Android) against RAAM 1.1 (Luxembourg Mobile Accessibility Assessment Framework). Use when reviewing existing mobile app code for accessibility compliance, generating audit reports, checking conformance levels, or preparing for Luxembourg accessibility certification. Covers all 15 themes with platform-specific test procedures. Default target: Level AA.
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。
Audit AI systems for bias with testing frameworks and mitigation strategies. TRIGGERS - Use when user needs help with ai-bias-auditor related tasks.
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。
Audit AI systems for bias and fairness. TRIGGERS - Use when user needs help with ai-bias-audit related tasks.
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。
Build AI audio transcription systems. TRIGGERS - Use when user needs help with ai-audio-transcriber related tasks.
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。
Build audit trails for AI decision-making. TRIGGERS - Use when user needs help with ai-audit-trail related tasks.
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。