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Found 197 Skills
Summarizes WeChat group chat highlights into a structured digest using the local wx-cli binary (https://github.com/jackwener/wx-cli). Generates a normal digest by default; a roast (毒舌) version is opt-in. Maintains per-group history (history.json + history-digests.jsonl) and per-user profiles across runs, with privacy guardrails baked in. Use when the user asks to "总结群聊", "群聊精华", "群聊摘要", "summarize group chat", "group chat digest", mentions a WeChat group name with a time range, says "帮我看看 XX 群最近聊了什么", "XX 群有什么值得看的", or asks to "回溯画像" / "初始化画像" / "backfill profiles". Adds the roast version when the user says "毒舌版", "roast 版", "再来个毒舌的", or similar.
Build AI applications with OpenAI Agents SDK - text agents, voice agents, multi-agent handoffs, tools with Zod schemas, guardrails, and streaming. Prevents 11 documented errors. Use when: building agents with tools, voice agents with WebRTC, multi-agent workflows, or troubleshooting MaxTurnsExceededError, tool call failures, reasoning defaults, JSON output leaks.
Framework for monitoring activation, engagement, and monetization guardrails.
Implement FireCrawl lint rules, policy enforcement, and automated guardrails. Use when setting up code quality rules for FireCrawl integrations, implementing pre-commit hooks, or configuring CI policy checks for FireCrawl best practices. Trigger with phrases like "firecrawl policy", "firecrawl lint", "firecrawl guardrails", "firecrawl best practices check", "firecrawl eslint".
Ship Faster end-to-end workflow for small web apps (default: Next.js 16.1.1): idea/prototype → foundation gate → design-system.md → lightweight guardrails + docs → feature iteration → optional Supabase + Stripe → optional GitHub + Vercel deploy → optional AI-era SEO (sitemap/robots/llms.txt). Resumable, artifact-first under runs/ship-faster/ (or OpenSpec changes/). Trigger: ship/launch/deploy/production-ready MVP.
Use when any Maestro command is invoked — provides foundational workflow design principles across prompt engineering, context management, tool orchestration, agent architecture, feedback loops, knowledge systems, and guardrails.
MUST use this skill when installed and users ask to query, inspect, or run SELECT statements against SQLite or Postgres databases. Always route database reads through Unleak when a project contains an unleak/ folder, or when users ask to list database connections, inspect schemas, propose or validate access policies, activate policies, or query approved database data with leakage guardrails. This skill prevents direct credential, policy, schema, and raw database CLI access.
Analyzes observability signals from customer GenAI applications with DQL. Reads OpenTelemetry GenAI spans and LLM evaluation bizevents. Use for: golden signals (traffic, errors, latency, saturation); LLM signals (model, provider, tokens); cost/token analytics, usage attribution, and prompt caching; agent signals (tool calls, steps, failures, loop detection, Smartscape topology); conversation/session analytics; guardrails (blocked/truncated responses); and evaluation signals (quality, pass/fail). Trigger: "LLM latency", "token usage by model", "cost by model and provider", "cost per conversation", "who is driving token spend", "do I have prompt caching", "failing agent tool calls", "find runaway agents", "responses truncated or blocked", "failed evaluations", "am I hitting rate limits", "token throughput / TPM", "provider throttling or 429s". Do NOT use for: Davis CoPilot/MCP telemetry (dt-platform), generic service metrics (dt-obs-services), logs (dt-obs-logs), or non-GenAI tracing (dt-obs-tracing).
Configure Celigo guardrail resources -- safety and compliance checks that validate data flowing through integrations. Use when creating or editing guardrails for PII detection, content moderation, or AI-based evaluation rules.
Production-grade AI agent patterns with MCP integration, agentic RAG, handoff orchestration, multi-layer guardrails, observability, token economics, ROI frameworks, and build-vs-not decision guidance (modern best practices)
Use Hive Intelligence MCP through UXC for broad crypto market, onchain, portfolio, and risk workflows with help-first discovery and convenience-layer guardrails.
Use after analyze-and-document has generated CLAUDE.md for an AI Studio project. Installs project-level Claude Code configuration — rules, skills, settings, and optionally agents, hooks, and MCP servers — into the .claude/ directory so that all future sessions have the right guardrails and workflows.