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Found 314 Skills
AnyGen: AI-powered content creation suite. Create slides/PPT, documents, diagrams, websites, data visualizations, research reports, storybooks, financial analysis, and images. Supports: pitch decks, keynotes, technical docs, PRDs, white papers, architecture diagrams, flowcharts, mind maps, org charts, ER diagrams, sequence diagrams, UML, landing pages, CSV analysis, earnings research, posters, banners, comics, and more. Also trigger when: 做PPT, 写文档, 画流程图, 做网站, 分析数据, 帮我调研, 做绘本, 分析财报, 生成图片, 做海报, 思维导图, 做个架构图, 季度汇报, 竞品调研, 技术方案, 建个落地页, 做个估值, 画个故事.
Use when the user wants to bootstrap a target codebase for AI-driven development with Claude Code. Generates a concise CLAUDE.md grounded in the actual stack (build tools, test runner, code style), creates a docs/ folder skeleton (designs/, prd/, plans/), and seeds conventions (conventional commits, plan-checkbox format, where designs and PRDs live). Triggers on "init Claude in this repo", "set up CLAUDE.md", "bootstrap docs folder", "prepare this project for Claude Code", "scaffold AI dev workflow", "/init this project".
Take a PRD and build a dark factory around it - a repository that takes work in as an issue and ships validated code out with nobody at the keyboard - one component at a time, into the user's actual repo. Covers the five components in construction order - the guidance layer, the validation harness, the workflow-driven repo, deployment, and the trigger that makes it autonomous - and is agnostic about which coding agent runs underneath (Claude Code, Codex, Archon, the Agent SDK, Cline, Goose, Amp, Pi). It encodes the AI coding process the user already runs rather than replacing it. Requires a PRD as input and deliberately does not write one. Use when the user wants to build a dark factory, an autonomous or self-driving repository, a software factory, an agent that ships its own code, an unattended or overnight coding loop, or asks how to get to level 4 or level 5 of AI coding autonomy; and when they mention dark factory, lights-out coding, autonomous PRs, or a repo that maintains itself.
Convert structured UX specs and product context into a sequenced prompts.md file for Claude Code. Use when a user has completed upstream design thinking (problem framing, PRD, UX spec) and needs to translate that into step-by-step prompts that coding agents can execute incrementally. This skill bridges design artifacts to code generation.
Run a structured business analysis workflow: requirements elicitation with stakeholder interviews and MoSCoW prioritization, as-is/to-be process mapping with BPMN notation, data-driven analysis (CBA, SWOT, root cause), and production-ready documentation (BRD, FRD, user stories with INVEST acceptance criteria). Triggers on "gather requirements", "write user stories", "map business process", "BRD", "FRD", "gap analysis", "cost-benefit analysis", "facilitate workshop", "business requirements", "process mapping", "as-is to-be", "stakeholder interview", or "business analyst". For management consulting (issue trees, steerCo business cases, operating model), use business-consultant—not business-analyst. For business model canvas, market sizing, and unit economics research, use business-model-researcher. Human data / labeling platform PRDs: product-management-human-data-platform. Monetization PRDs and packaging: product-management-monetization.
Framework (OSS). Entry point and router for every Expo or EAS task. Load this skill first — before writing code and before choosing another expo-* / eas-* skill — when the request, PRD, or spec mentions Expo, EAS, Expo Go, or an expo-* package, or the project has an `expo` dependency in `package.json`. Within that gate it also covers app specs and designs to implement (tabs, stacks, maps, lists, navigation, building from a screenshot), and phrasings like 'implement a mobile app', 'make my app look native', 'add navigation', 'fetch some data', 'upgrade my SDK', 'add Expo to my existing native app', 'ship to the App Store', or 'I'm new to Expo, where do I start'. A fully specified request (SDK pinned, libraries named, layout given) still routes through here — the shared setup rules still apply. Do NOT load it when neither signal is present: a bare React Native project with no `expo` dependency is not Expo work. Detects the real goal, routes to the right expo-* / eas-* skill, and owns the shared setup rules.
Write the go-to-market communication for a chosen segment using Ivan Zamesin's AJTBD / Next Move Theory methodology. Input — a /nmt-craft-value-proposition result (best), a /nmt-product-requirements PRD, a /nmt-market-research result, or a manual segment+Jobs description. Output — ready-to-publish landing-page copy, ad/creative copy built on the seven Job-language formulas, and a GTM/growth plan — channel hypotheses, lead magnets, viral loops, cross-sell / upsell / retention messaging. Everything is communicated through the Big Job (motivation), in concrete success criteria not adjectives, with features as proof not message. Use when the user wants landing copy, ad copy, creatives, channel hypotheses, or a launch plan — "write the landing / the copy / the go-to-market". Two modes — Quick (default, no internet) and Deep (subagents + web for real review language). Plain language; defaults to English.
Use AI to write NEW test code from specs, PRDs, user stories, code diffs, bug reports, or OpenAPI specs. Staged pipeline: requirements extraction → risk analysis → coverage matrix → scenario generation → oracle design → test code → human review, with guardrails against hallucinated APIs and weak assertions. Use when: "generate tests from spec," "tests from PRD," "tests from user story," "auto-generate test cases," "AI write tests for me." Not for: testing AI/LLM features in your product — use ai-system-testing. Not for: auditing a pre-existing test suite you did not just generate — use ai-qa-review (Step 7 here only reviews tests THIS pipeline produced). Related: playwright-automation, unit-testing, api-testing, qa-project-context.
Set up your project's global rules, a lean and well-structured root CLAUDE.md (plus a starter .claude/), following the course methodology. Greenfield: pass your PRD and/or architecture-spec path and it derives rules from your engineering decisions (a PRD alone is product context). Brownfield: leave it blank to derive from your primed codebase (run /prime-codebase first), or pass a codebase-analysis doc for a large repo. Use when initializing or re-deriving the AI Layer's rules, onboarding a codebase, or replacing a generic /init output. The customizable replacement for /init.
Case Radar. Given a new thing (new tool/new concept/new ecosystem), scan the ecosystem to find interesting real-world cases, focusing on capturing "authentic assets" (screenshots/source code/demos) instead of GitHub homepage, and output a browsable HTML case collection. Triggered when users say "See what people are doing with X", "Scan the X ecosystem", "What new ways are there to use X in the market", "Show me authentic cases of X", or "/case-radar". Not suitable for: ① In-depth research with clear objectives (use long-research) ② Writing articles/creating PRDs (use writing-assistant / prd-doc-writer) ③ Pure knowledge-seeking without needing HTML (just ask directly).
Generate long HTML articles for human reading — organize existing materials, experiences, and data clearly before writing. Each time it is triggered, first use AskUserQuestion to clarify 4 key parameters in one go: [Who is it for / What will readers gain after reading / Depth level / Style + Focus], then output according to the 6-stage framework. **The only output format is HTML** — this skill should not be used if the user requests markdown or direct chat responses. It is triggered when the user says phrases like "do a retrospective", "summarize this", "compile into HTML", "create a tutorial/study guide", "explain X clearly", etc., which require structured reading content of over 500 words. It is not applicable for: project plan reports/framework plans/version roadmaps (use issue-pool, which has built-in md2html), PRDs/requirements documents/test cases (use prd-test-writer), interface design drafts (use design-exploration), naming (use product-naming), writing code/fixing bugs/modifying files, or questions that can be answered in one or two sentences.
Guide users to thoroughly study an article/document and truly master it (not just generate a summary). Five steps: Extract key insights → Divide into sessions → Run the "Learn-Test-Teach" cycle for each session → Connect to user's scenarios → Practical operation + Quiz + Explain wrong answers + Distill learnings. Each session produces HTML courseware + documented notes; a quiz is mandatory after each session, and you must correct any inaccuracies in the user's retelling; abstract concepts can be demonstrated interactively (clickable and executable); use the user's own business scenarios as cases throughout; generate auto-graded quizzes with multiple question types after learning, and finally distill the learnings back into the user's tools. The core trigger is when the user wants to "learn" rather than "get a result", such as "Let's study this article/link together", "Teach me", "Intensive reading", "I want to learn X", "I don't understand this article, please explain it to me". Start directly when there are specific materials (links, local files, PDFs, or the user's own skill/document/code); if there is only learning intent but no materials, still use this skill, but the first thing to do is confirm the materials with the user, and never teach based on memory. Not applicable for: Only needing a summary/abstract/tutorial article where the user reads it and finishes without needing to answer questions (use readable-output), just collecting information for research (use available web/platform material collection tools), asking to write PRD/test cases (use prd-test-writer), and when the user actually wants you to do the task directly (just do it then).