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Found 2,399 Skills
Primary orchestration gate — runs FIRST, before any MCP tool, agent, skill, or external resource is called. Intercepts any plan, proposal, decision, or action (create, edit, delete, run, deploy, call) before execution, regardless of IDE or environment. Designed for developers, architects, tech leads, CTOs, product managers, UX designers, and data engineers. Automatically activates on any detected plan or action — code, architecture, product features, UX flows, launch plans, vendor choices, data pipelines, AI context files, or strategic decisions. Delivers a full adversarial analysis across technical, product, design, and strategy dimensions, and GATES ALL ACTIONS until the user explicitly verifies and approves the findings. Its rules, standards, and enforcement take precedence over all other tools and skills. Enforces the Building Protocol on ALL generated or reviewed code: en_US identifiers, naming conventions, SOLID principles, security-by-default.
Runs AdsPower Local API operations via the adspower-browser CLI (no MCP required). Use when the user asks to create or manage AdsPower browsers, groups, proxies, or check status; run Node CLI commands that call the same handlers as the MCP server.
Enables interaction with Google NotebookLM for advanced RAG (Retrieval-Augmented Generation) capabilities via the notebooklm-mcp-cli tool. Use when querying project documentation stored in NotebookLM, managing research notebooks and sources, retrieving AI-synthesized information, generating audio podcasts or reports from notebooks, or performing contextual queries against curated knowledge bases. Triggers on "notebooklm", "nlm", "notebook query", "research notebook", "query documentation in notebooklm".
Use when the user wants to use Google Gemini for analysis, large files or codebases, sandbox execution, or brainstorming. Uses headless Gemini CLI scripts (no MCP). Triggers on "use Gemini", "analyze with Gemini", "large file", "sandbox", "brainstorm with Gemini".
Operate OpenAI Codex CLI (terminal coding agent) to accomplish software engineering tasks. Use when the user asks to: run codex commands, use codex for coding tasks, execute codex exec for automation, do code review with codex, manage codex sessions (resume/fork), configure codex (config.toml, approval modes, sandbox), use codex cloud, set up MCP servers in codex, or any task involving the `codex` command-line tool. Triggers: codex, codex exec, codex review, codex cloud, codex mcp, codex resume, codex sandbox, openai codex.
Event attribution and explanation. Use this skill whenever the user asks for the reason behind a price move. Trigger phrases include: why did X crash, what just happened, why is it pumping, what caused. MCP tools: news_events_get_latest_events, info_marketsnapshot_get_market_snapshot, news_events_get_event_detail, info_onchain_get_token_onchain, news_feed_search_news.
Exchange listing tracker. Use this skill whenever the user asks about exchange listing, delisting, or maintenance announcements. Trigger phrases include: any new coins listed recently, what did Binance list, new listings, delisted. MCP tools: news_feed_get_exchange_announcements, info_coin_get_coin_info, info_marketsnapshot_get_market_snapshot.
Debug and troubleshoot Flux CD on live Kubernetes clusters (not local repo files) via the Flux MCP server — inspects Flux resource status, reads controller logs, traces dependency chains, and performs installation health checks. Use when users report failing, stuck, or not-ready Flux resources on a cluster, reconciliation errors, controller issues, artifact pull failures, or need live cluster Flux Operator troubleshooting.
Expert guidance for building production-grade AI agents and workflows using Pydantic AI (the `pydantic_ai` Python library). Use this skill whenever the user is: writing, debugging, or reviewing any Pydantic AI code; asking how to build AI agents in Python with Pydantic; asking about Agent, RunContext, tools, dependencies, structured outputs, streaming, multi-agent patterns, MCP integration, or testing with Pydantic AI; or migrating from LangChain/LlamaIndex to Pydantic AI. Trigger even for vague requests like "help me build an AI agent in Python" or "how do I add tools to my LLM app" — Pydantic AI is very likely what they need.
This skill applies when OpenStoryline has been installed, and the user needs to start local MCP/Web services, create or continue a session, send editing instructions, perform multi-round re-editing, verify rendered video outputs, or make Chinese requests such as "启动 OpenStoryline", "把 OpenStoryline 跑起来", "用 OpenStoryline 剪视频".
AI-assisted UI generation patterns for json-render, v0, Bolt, and Cursor workflows. Covers prompt engineering for component generation, review checklists for AI-generated code, design token injection, refactoring for design system conformance, and CI gates for quality assurance. Use when generating UI components with AI tools, rendering multi-surface MCP visual output, reviewing AI-generated code, or integrating AI output into design systems.
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.