3,602 件 ・ 関連度順
概要と使いどころ
Improves Agent Skills via validate → rule-based eval cases → plugin-eval → prompt evals → bounded edits with held-out gates. Use when tuning skill quality, routing, or adopting Chrome/Microsoft T-named quality gates—not for bulk validate-only or SkillOpt automation.
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。
Execute tasks based on GitHub Issue content
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。
Create an implementation plan and a GitHub Issue based on the task description provided as an argument. Use this when the user supplies a natural-language task description (not an issue number) and wants a new implementation-ready Issue. If the input is an existing issue number, use create-issue-from-issue-number (re-analyze) or update-issue (reflect comments) instead.
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。
Update an existing GitHub Issue's description based on the issue number. Reads all issue comments and reflects any items not yet captured in the description. After refreshing the description, reviews it for remaining ambiguities or unclear requirements and posts any open questions as a follow-up 確認事項 comment.
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。
Re-analyze an existing GitHub Issue using its current title and body as input, refresh the implementation plan against the latest code state, and update the Issue in place. Use this when the user provides an Issue number (numeric, `#`-prefixed, or Issue URL) and wants to regenerate the Explore-based analysis. For reflecting comment-driven updates instead, use update-issue. For creating a brand-new Issue from a natural-language task description, use create-issue.
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。
Project-level visual direction skill for WeChat Official Account articles. Use when planning, improving, diversifying, generating, or reviewing cover images and body illustrations for公众号文章, especially when Codex image generation should be used without being constrained by repetitive preset-based illustration 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。
Record browser or Web UI interaction demos as optimized GIFs using the available built-in browser, state-based frame capture, and deterministic encoding, then publish to a dedicated assets branch when the task includes attaching the GIF to a pull request. Use when asked to make, record, or generate a GIF that demonstrates a browser workflow, and for every pull request that changes product-user-visible GUI behavior, which MUST include a GIF recorded from the pull request's real server and model flow.
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 Lingzao creator-content tools for Xiaohongshu/XHS, Douyin, and WeChat official-account public content. Lingzao supports XHS SEO, Xiaohongshu account analysis, benchmark account discovery, viral note breakdown, keyword research, one-stop content packages from keyword/link/image/inspiration material, title and cover optimization, hand-drawn route-map cards, city food maps, travel itinerary maps, life checklist maps, workflow manual maps, creator content workflow, note search, creator search, profile lookup, recent posts, deep profile copy/subtitle analysis, note/article detail, post comments, article stats, related articles, short-video copy extraction, and prompt-based creator image generation.
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 a piece of work based on a spec or set of tickets.
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。
Phase 2 of disease-market-sizing-orchestration. Discovers disease-specific stratification dimensions by citing guideline sections from sources/guidelines/. ALWAYS uses cite-based discovery — NEVER built-in stratification templates. Output: .cache/<slug>/staging.json. Use AFTER contract-elicitor and AFTER A1' guidelines fetch.
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。
Evidence-grounded AI research workflow for turning supplied economics, finance, management, and social-science papers or structured records into versioned PaperReading artifacts. Use when Codex must ingest text, Markdown, or a text-based PDF; separate source-grounded claims from researcher analysis; bind findings to evidence IDs and locators; review extraction candidates; migrate v0.2 PaperRecord JSON; validate or verify a v0.3 PaperPackage; generate research extensions; export reviewable JSON or Markdown; or safely update a compatible 13-field literature workbook.
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 repeatable data-to-Docs pipelines from Sheets and Drive sources. Use for automated status reports, template-based document assembly, and scheduled publishing 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。
GodoMaster — Godot 4.x game development intelligence: GDScript, nodes/scenes, 2D/3D rendering, physics, animation, UI, audio, input, shaders, networking, performance, export, file I/O, testing, localization, AI behavior, asset pipeline, and architecture tooling. Complete workflow for indie and professional game development based on official Godot 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。
Run user-authorized black-box web security tests and evidence-based reports. Use for 黑盒安全测试、渗透测试、数据泄露、未授权访问、公开 JS/API、登录爆破防护、CORS 或安全响应头检查。
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。
Produces a deep, honest peer-review of how someone uses Claude Code by statistically analyzing their local session data (~/.claude/usage-data/ and ~/.claude/projects/). Trigger whenever the user asks to review, analyze, audit, or critique their own Claude Code usage, workflow, habits, or skill level — including phrases like "analyze my cc usage", "review my cc sessions", "peer review my cc workflow", "deeper than /insights", or any ask for an honest audit of their AI workflow. Also covers portfolio/hiring-manager framings (e.g. "portfolio for Anthropic/OpenAI/xAI"), but ALWAYS ask the user in Step 0 which version to build (self / hr / both) before running — never silently produce an HR report, because that version goes to outsiders and needs explicit privacy setup. The HTML report is laid out ledger-first for SELF (opening band, output/team/leak/trend ledgers, then peer review, 9-dim scoring, try-this-week, case study, claim-indexed evidence). The HR variant is a recruiter version v1: identity card, earned badges (threshold-based, earned-only), allowlist-filtered output ledger, one case study, and a methodology & scope disclosure — no scores, no peer-review memo, no charts.
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。
Appwrite CLI skill. Use when managing Appwrite projects from the command line. Covers installation, login, project initialization, multi-file project configuration, deploying functions/sites/tables/buckets/teams/webhooks/topics, flag-based list queries, non-interactive CI/CD mode, and generating type-safe SDKs.
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。
Appwrite TypeScript SDK skill. Use when building browser-based JavaScript/TypeScript apps, React Native mobile apps, or server-side Node.js/Deno backends with Appwrite. Covers client-side auth (email, OAuth, anonymous), database queries, file uploads, real-time subscriptions, and server-side admin via API keys for user management, database administration, storage, and functions.
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。
Structural simplicity review based on Rich Hickey's "Simple Made Easy" framework. Trigger when: - Reviewing code for complected concerns, analyzing coupling, or simplifying code architecture. - Prompt contains: /hickey, simple made easy, complect, decouple, compose.
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。
Volatility-based decomposition review. Trigger when: - Evaluating module boundaries against axes of change and business volatility. - Prompt contains: /lowy, volatility, axis of change, design decomposition, boundary.
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 coaching hypothesis-driven debugging that requires the learner to gather evidence and reason about root causes before applying fixes.
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。
Solves complex, open-ended problems using an evolutionary search mechanism inspired by genetic algorithms. Generates a diverse population of candidate answers, scores them against a rubric, then iteratively applies selection, crossover, and mutation to breed progressively better solutions. Use this skill whenever the user wants to explore a solution space deeply, asks for the "best" answer to a subjective or multi-dimensional problem, wants to evaluate competing approaches and distill the strongest, or uses any of these triggers: "evolutionary search", "genetic algorithm", "evolve an answer", "breed solutions", "population-based search", or phrases like "give me multiple approaches and refine the best one". Also trigger when the problem is complex, open-ended, or has no obvious single correct answer and the user wants a high-quality, well-explored result, not just a quick response.
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。
Efficiently extract and convert the contents of any local file—such as PDF, DOCX, DOC, ODT, RTF, XLSX, XLS, or HTML—into clean, well-formatted markdown saved to disk. Use this skill whenever the user requests to parse, read, or extract information from a file on their computer, including phrases like “parse this PDF”, “convert this document”, “read this file”, “extract text from”, or when a local file path (not a URL) is provided. This skill offers advanced options like generating AI-powered summaries and answering questions based on the file's content. Prefer this tool over `scrape` when handling local files to deliver precise, structured outputs for downstream 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。
First-principles strategy — strip away conventional assumptions and find the theoretical maximum for your business. Three modes. Diagnostic mode runs a full session (45+ min) to define your theoretical maximum, map the gap honestly, classify constraints, invert for failure modes, set strategic intent, and work backwards to your first intervention. Review mode (15-20 min) checks whether your theoretical maximum has shifted, whether the gap has changed, and whether you're still climbing the right peak. Alert mode defines constraint-shift, peak-shift, and local-peak triggers that tell you when to reassess. Use when someone is stuck optimising incrementally, when conventional wisdom is driving strategy, when a new technology or regulation changes what's physically possible, or when you suspect the business is climbing a local peak. Integrates with company-context.md. Based on practice by Eterdis (eterdis.com).
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。
Continuous environmental scanning across six PESTEL categories — Political, Economic, Social, Technological, Environmental, Legal. Not a one-time analysis but an ongoing radar. Three modes. Diagnostic mode runs a full scan and prioritises forces by impact, speed, and reversibility. Review mode checks the watch list monthly for movement and new signals. Alert mode defines concrete monitoring triggers for each top force. Use whenever someone wants to understand external forces acting on their business, assess macro risk, prepare for planning, or check whether the world has moved since last time they looked. Connects to the strategy map (forces act on the chain) and Wardley Map (forces drive component evolution). Based on practice by Eterdis (eterdis.com).
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。