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Found 2,081 Skills
End-to-end onboarding for a freshly-plugged-in M5Stack ESP32 device (Cardputer, Cardputer-Adv, Core, CoreS3, Stick) — detect on USB, flash UIFlow 2.0 firmware, and install the Claude Buddy MicroPython app bundle. Use whenever the user plugs in or wants to flash/provision/reset an M5Stack or ESP32 board, or says "m5-onboard go".
Use when the user wants to author, refine, or audit a Product Requirements Document for AI coding agents. Walks through an 8-phase pipeline (Socratic discovery → PRD draft → acceptance criteria → adversarial review → task decomposition → AI-readiness gate → test generation → handoff). Triggers on "write a PRD", "spec this feature", "draft requirements", "prepare X for Claude/Cursor/Copilot/Windsurf/Aider to build", "audit my PRD", "is this PRD AI-ready", "score this spec".
Groundwater time series analysis and modelling using transfer function noise models. Use when Claude needs to: (1) Analyze groundwater level time series, (2) Model well responses to precipitation/pumping, (3) Calibrate aquifer parameters from head data, (4) Forecast or hindcast groundwater levels, (5) Decompose hydrological signals into components, (6) Compare response functions, (7) Perform model diagnostics and uncertainty analysis.
Multi-method geophysical modelling and inversion framework. Use when Claude needs to: (1) Perform electrical resistivity tomography (ERT) inversion, (2) Run seismic refraction tomography (SRT), (3) Model induced polarization (IP) data, (4) Simulate ground penetrating radar (GPR), (5) Create finite element meshes for geophysical problems, (6) Perform joint inversions of multiple datasets, (7) Forward model geophysical responses, (8) Analyze time-lapse monitoring data.
Use ARIS (Auto-Research-In-Sleep) for autonomous ML research — idea generation, paper review, experiment automation, and cross-model collaboration with Claude Code, Codex, or any LLM agent.
Generate a fully working React + Vite app that explains a codebase's workflows, data types, and architecture through interactive visuals — click-to-step animated walkthroughs with auto-play, sequence diagrams, animated packet tracers, message inspectors that toggle between named-field view and raw JSON, and collapsible code peeks with file:line citations. Splits the repo into 4–6 domain clusters and dispatches one content agent per cluster to write the pages in parallel. The skill bundles its own reference pages (under references/examples/) so it works in any repo. Use this skill whenever the user asks for interactive docs, animated explainers, an "agent team" for docs, one page per domain, wants to visualize a system's request flow or wire protocol, or any visual documentation site. Requires CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 in .claude/settings.json.
Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.
Answer ZenMux questions by reading the latest official docs. Use for product features, APIs, integration, pricing, models/providers, routing, fallback, streaming, multimodal, structured output, tool calling, reasoning, prompt caching, image/video generation, web search, long context, observability, logs, cost tracking, subscriptions, PAYG, invoices, FAQ, privacy, terms, compliance, and tool guides for Claude Code, Cursor, Cline, Codex, Gemini CLI, opencode, Cherry Studio, Obsidian, Sider, Open-WebUI, Dify, and GitHub Copilot. Trigger on "ZenMux docs", "ZenMux API", "how to use ZenMux", "models", "pricing", "ZenMux 怎么用", "文档", "快速开始", "API 参考", "模型路由", "供应商路由", "订阅", "按量计费", "接入", "配置". Also use when ZenMux is the project context and the user asks about LLM API aggregation, model routing, or provider fallback.
Configure the project's game engine and version. Pins the engine in CLAUDE.md, detects knowledge gaps, and populates engine reference docs via WebSearch when the version is beyond the LLM's training data.
Initialize or migrate a repo into the ai-memory pattern: the .ai-memory.toml routing marker (workspace/project), the recall/write routing snippet in CLAUDE.md/AGENTS.md, and the ai-memory MCP server entry. Includes the qmd→ai-memory migration for repos still on the old wiki/qmd stack. Use when the user asks to set up ai-memory in a project (greenfield or brownfield), wire the MCP, enable auto-capture, or migrate off qmd.
Audit a live page for accessibility issues and locate each violation precisely — optionally pass a URL (e.g. `accesslint:scan https://example.com/dashboard`), otherwise ask for one. Ensures a debuggable Chrome, runs the @accesslint/core engine via CDP, and returns a worklist of live-DOM WCAG violations grounded to each violation's DOM selector and source file:line. Locates; doesn't edit — output drives fixes by Claude. Use it for "is this page accessible", or to verify a UI change. For diffing against uncommitted changes or a branch, use the `diff` skill.
Edit a vigiles .spec.ts to change a compiled instruction file (CLAUDE.md / AGENTS.md) — add, modify, or remove a rule, section, command, or key file. Use whenever you need to change a CLAUDE.md/AGENTS.md that carries a vigiles hash (edit the spec, never the artifact), including adding a new enforce()/check()/guidance() rule.