Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Agent workflows
Use when complex problems require systematic step-by-step reasoning with ability to revise thoughts, branch into alternative approaches, or dynamically adjust scope. Ideal for multi-stage analysis, design planning, problem decomposition, or tasks with initially unclear scope.
Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.
Benchmark CodeGraph retrieval quality on a real codebase by comparing agent behavior with vs without CodeGraph. Use when the user runs /agent-eval or asks to test, benchmark, audit, or validate a codegraph version (the local dev build or a published npm version) against a language's repo.
Use this skill for any web task where WebFetch or curl would fail or be insufficient — pages that require JavaScript to render, forms to fill and submit, screenshots or PDFs of live pages, CAPTCHA/bot-protection bypass, login flows, and multi-step browser navigation with persistent session state. WebFetch returns empty HTML for JS-rendered pages; this skill runs a real cloud browser that executes JavaScript, maintains cookies, clicks buttons, and handles anti-bot measures. Trigger when the user wants you to actually perform a web task (visit, interact, extract, capture) rather than just write code for it. Skip only for: static pages a simple GET can fetch, localhost or private-network targets, writing browser automation code the user will run themselves, or conceptual questions about browser tools.
Show how much context window context-mode saved this session. Displays token consumption, context savings ratio, and per-tool breakdown. Read-only — shows stats only, no reset capability. To wipe the knowledge base entirely, use ctx_purge instead. Trigger: /context-mode:ctx-stats
Use the PlanetScale CLI (pscale) from automated agents with --format json, auth check, pscale sql, and per-command --force. Run before other PlanetScale skills when driving pscale directly. Use when the user asks to automate pscale, run CLI commands headless, or verify pscale auth from an agent.
Review pull requests for the MiniMax Skills repository. Use when reviewing PRs, validating new skill submissions, or checking existing skills for compliance. Run the validation script first for hard checks, then apply quality guidelines for content review. Triggers: PR review, pull request, validate skill, check skill.
Use when building, editing, validating, testing, or debugging an n8n workflow through the n8n-mcp MCP server—designing a flow, configuring a node, writing an expression or Code node, wiring credentials, or fixing one that misbehaves. The entry-point skill for the n8n-mcp-skills pack: it routes you to the right specialist skill, gives working knowledge of every n8n-mcp tool from turn one, and states the rules that keep workflows from breaking in production. Always consult it first on any n8n, workflow, node, or automation task—even a quick one-off, and even when the user names no skill—because n8n's surface drifts between versions and the specialist skills prevent silent failures.
Analyzes user-requested Screenpipe history windows to detect repeated research workflows, match existing scientific skills, and stage new skill drafts or composition recipes for review. Requires a reachable Screenpipe HTTP API, normally on localhost:3030. Detection and embedding inference run locally; the selected LLM receives redacted app/title cluster summaries and matched skill descriptions. Use only when the user explicitly asks to analyze their recent work and propose skills.
Summarize recent compound-engineering plugin releases, or answer a specific question about a past release with a version citation. Use when the user types `/ce-release-notes` or asks "what changed in compound-engineering recently?" or "what happened to `<skill-name>`?".
Ralph Wiggum-inspired automation loop for specification-driven development. Orchestrates task implementation, review, cleanup, and synchronization using a Python script. Use when: user runs /loop command, user asks to automate task implementation, user wants to iterate through spec tasks step-by-step, or user wants to run development workflow automation with context window management. One step per invocation. State machine: init → choose_task → implementation → review → fix → cleanup → sync → update_done. Supports --from-task and --to-task for task range filtering. State persisted in fix_plan.json.
SB Leader encouragement mode — an emotionally attuned, well-paced ENFP leader. The underlying behavior remains unchanged (three red lines and methodology), while the narration shifts from pressure to empathy and encouragement, with occasional playful teasing. Triggers on: '/pua:yes', '夸夸模式', '唠嗑模式', '情绪价值', 'yes', '夸我', '鼓励模式'.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Build local constrained-browser agents with a safe_browser tool that owns CDP, enforces a domain allowlist with Fetch interception, and lets a runtime Claude Agent SDK agent complete browsing tasks without raw browser, shell, or CDP access. Use when the user wants an agent to browse or scrape while staying on approved domains, demo blocked off-domain navigation, or generate a safe browser client.
AI-native tutor and onboarding workflow for the MCPA (Model Context Protocol Associate) certification in AI Engineering from Scratch. Use when a learner wants to prepare for the MCPA, resume their certification path, learn the next lesson interactively, run and verify practical labs, take the diagnostic or a full mock, or remediate weak exam domains from GitHub with Claude Code, Codex, ChatGPT, Cursor, or another agent.
Adds the product layer to a repository that om-setup-agent-pipeline already configured — one yes per product role, a discovery block in .ai/agentic.config.json, the Discovery stage, Definition of Ready, product roles, and protected product decisions appended to SDLC.md between markers, the research directory, and a routing row in AGENTS.md. Run once; re-run with --refresh. No product skill requires it.
Write JavaScript or Python for the n8n Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode) — the AI-agent-callable tool, NOT the workflow Code node. Use when building a Code Tool attached to an AI Agent, writing code that an LLM will invoke, parsing the `query` input, returning a string result, defining an input schema for structured arguments (specifyInputSchema, jsonSchemaExample, DynamicStructuredTool), or troubleshooting errors like \"Wrong output type returned\", \"No execution data available\", \"The response property should be a string, but it is an object\", \"Cannot assign to read only property 'name'\", or an AI agent that refuses to call the tool. Covers the critical differences between Code node and Code Tool: return format (string vs `[{json:{...}}]`), unavailability of `$fromAI`/`$input`/`$helpers` in the Code Tool sandbox, naming rules for AI invocation, and when to use `toolWorkflow`/HTTP Request Tool instead
Manage context-mode GitHub issues, PRs, releases, and marketing with parallel subagent army. Orchestrates 10-20 dynamic agents per task. Use when triaging issues, reviewing PRs, releasing versions, writing LinkedIn posts, announcing releases, fixing bugs, merging contributions, validating ENV vars, testing adapters, or syncing branches.
Enable and configure Moltbot/Clawdbot memory search for persistent context. Use when setting up memory, fixing "goldfish brain," or helping users configure memorySearch in their config. Covers MEMORY.md, daily logs, and vector search setup.
超压缩 communication mode。Cuts token usage ~75% by dropping filler, articles, and pleasantries while keeping full technical accuracy. Use when user says “caveman mode”, “talk like caveman”, “use caveman”, “less tokens”, “be brief”, or invokes /caveman.
Submit locally modified `skills/<skill-name>/` as a PR to an upstream repository (such as Fandhe-AI/agent-cli-skills). Read `source` from `skills-lock.json`; a safety check blocks pushes to repositories outside `Fandhe-AI/`. Run clone → apply changes → security check → create branch → push → `gh pr create`. After merging, update the hash with sync-skills-lock. Use for requests such as “contribute a skill upstream” or “open a PR to an external repository.”
Iris is Redis's umbrella for AI-focused products. Use this skill when integrating with the Iris Redis Agent Memory (RAM) data plane on Redis Cloud — recording session events for an AI agent, creating or searching long-term memories, configuring a memory store, or tuning background memory promotion. Code examples use the official `redis-agent-memory` (Python) and `@redis-iris/agent-memory` (TypeScript) SDKs.
MUST be used when adding AI, Atlas, an agent, a chat UI, or LLM features to a Flows/Fusion app. Use the Atlas/EOS sidebar via @cognite/app-sdk — not useAtlasChat, vendored atlas-agent, or per-row chat completions. Triggers: atlas, EOS, PAIA, agent chat, chat UI, sendAgentMessage, sendAgentLayoutMode, registerAgentServer, connectToHostApp, useAtlasChat, LLM. In-app chat: integrate-atlas-chat only if the host sidebar cannot work.
Use when building features with Claude Code in any codebase and the work should go through a disciplined build → review → test → fix loop. Triggers on "run the build loop", "build the next task", "continue the plan", "build this feature properly", or any request to implement work from a plan file or a direct feature prompt. Builds from the plan (or the prompt if no plan exists), runs Claude Code's `/review` (plus `/security-review` for sensitive surfaces) and fixes every issue found, tests and verifies the feature end to end, fixes anything testing surfaces, and reports back once complete. Repeats until all plan tasks are checked off.
Explicitly save important knowledge to auto-memory with a timestamp and context. Use when the user says “remember this”, asks you to capture a lesson so you stop repeating a mistake across sessions, or when a discovery is too important to rely on auto-capture.
Platform-neutral guidance for using Open Computer Use, the open-source Computer Use MCP server and CLI for macOS, Linux, and Windows. Use when an agent needs to install, verify, troubleshoot, configure, or operate Open Computer Use through its native CLI, stdio MCP server, or direct Computer Use tool calls.
Use this skill proactively when the user indicates they are done working, ending the session, wrapping up, or saying goodbye. Also use when significant work has been completed and the user hasn't explicitly asked to continue. Analyzes the session to evolve skills/commands/agents and propagates useful project permissions to global settings.
Build conversational AI voice agents on the ElevenLabs platform. Configure agent + tools + knowledge base, integrate SDK (React / React Native / Swift / JS / server-side), test, deploy. Use whenever the user mentions ElevenLabs, building a voice agent, an AI phone system, an AI receptionist, conversational AI, or troubleshooting deprecated @11labs packages, webhook errors, CSP violations, localhost allowlist, or tool parsing errors.
Turn a reference video into a highly detailed recreation or inspiration prompt. Use when the user provides, mentions, uploads, links, or points to a video and asks to analyze the design, UI, animations, transitions, scroll interactions, typography, colors, assets, WebGL/Three.js, storytelling, section-by-section behavior, or to create a prompt/article that recreates the page, app, interaction, or motion system.
Use inside a product repository when the user wants the full MVP built from their BuilderOS spec documents. Triggers on phrases like "build my MVP", "build the app", "execute the roadmap", "start the build", "work through the whole roadmap", "build everything", or any request to implement the entire plan rather than a single task or phase. Requires `docs/prd.md` and `docs/product-roadmap.md` (plus `docs/product-vision.md` and `docs/design.md` for context). Works through every roadmap task in order — implementing, testing, and verifying each before moving on, marking checkboxes and updating the status line — and runs until all tasks are complete and the magic moment works end to end, then initializes git with an initial commit and offers to connect a remote repo.
Security guidelines for LLM applications based on OWASP Top 10 for LLM 2025. Use when building LLM apps, reviewing AI security, implementing RAG systems, or asking about LLM vulnerabilities like 'prompt injection' or 'check LLM security'. IMPORTANT: Always consult this skill when building chatbots, AI agents, RAG pipelines, tool-using LLMs, agentic systems, or any application that calls an LLM API (OpenAI, Anthropic, Gemini, etc.) — even if the user doesn't explicitly mention security. Also use when users import 'openai', 'anthropic', 'langchain', 'llamaindex', or similar LLM libraries.
Check for qwencloud-ai updates and notify the user when a new version is available. TRIGGER when: user asks to check for updates, check version, asks 'is there a new version', 'latest version', 'update skills', 'check update', or any other qwen skill delegates to this skill, or user explicitly invokes this skill by name (e.g. use qwencloud-update-check). DO NOT TRIGGER when: non-update-related tasks, general version questions about other software.
Generate text, have conversations, write code, reason, and call functions with Qwen models and third-party models available on QwenCloud. TRIGGER when: user asks to chat with Qwen, generate text, write code with Qwen, use Qwen function calling, call third-party models (deepseek, kimi, glm, etc.) via QwenCloud, or explicitly invokes this skill by name (e.g. use qwencloud-text). DO NOT TRIGGER when: using non-QwenCloud platforms (direct OpenAI API, Google Gemini API, etc.), general coding questions unrelated to QwenCloud, image/video understanding (use qwencloud-vision), image/video/audio generation.
Claude as the trainer. Walks an SMB owner through connecting their first two tools, runs one recipe to prove immediate value, interviews them about their business (industry, size, top three headaches), stores that context persistently so every other skill benefits, and sets a weekly check-in cadence. Use when the owner is getting started or says any of: "set me up," "setup," "help me get set up," "get started," "help me get started," "get me started," "what can you do," "I'm new to this," or is in their first session.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.