Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Agent workflows
Use when tackling complex reasoning tasks requiring step-by-step logic, multi-step arithmetic, commonsense reasoning, symbolic manipulation, or problems where simple prompting fails - provides comprehensive guide to Chain-of-Thought and related prompting techniques (Zero-shot CoT, Self-Consistency, Tree of Thoughts, Least-to-Most, ReAct, PAL, Reflexion) with templates, decision matrices, and research-backed patterns
Use when a developer wants to build their first CopilotKit Channels agent and get it answering in Slack or Microsoft Teams: "set up a channel", "connect my agent to Slack", "get my agent into Teams", or starting from nothing and wanting a working channel end to end. Covers the whole path: inspecting or scaffolding the project, building the AG-UI agent, creating and reconciling the managed Channel with the public CopilotKit CLI, running the long-running host, and proving a real provider mention gets a reply. The workflow is not in this file. Run `npx --yes copilotkit@latest onboard start` and follow the graph it prints.
Interactively create, install, activate, and verify custom claude-mem modes, including domain-specific observation types, concept tags, optional Telegram alerts, bot setup, worker restart, and startup-context verification. Use whenever someone asks to customize what claude-mem remembers, create or change a mode, track domain-specific notes, add observation types or tags, or send Telegram notifications for particular memories—even if they do not use the word “mode”
Lightpanda browser, a drop-in replacement for Chrome-based browsing in any AI agent — faster and lighter for tasks without graphical rendering, such as data retrieval. Use it via MCP server, CLI fetch, or CDP with Playwright/Puppeteer — or run/save automations as deterministic, token-free replay scripts (PandaScript) via its own agent mode.
Generate and install a custom Claude Code status line with selectable columns (model, context, effort level, git, dir, worktree, vim) and a color theme. Context and effort elements color-change based on level. Triggers on "status line", "statusline", "customize status", "status bar", "effort level display", "状态栏", "ステータスライン", or similar.
Integration patterns for Mapbox MCP Server in AI applications and agent frameworks. Covers runtime integration with pydantic-ai, mastra, LangChain, and custom agents. Use when building AI-powered applications that need geospatial capabilities.
Designs or reviews CLIs so coding agents can run them reliably: non-interactive flags, layered --help with examples, stdin/pipelines, fast actionable errors, idempotency, dry-run, and predictable structure. Use when building a CLI, adding commands, writing --help, or when the user mentions agents, terminals, or automation-friendly CLIs.
Turn any MCP server, OpenAPI spec, or GraphQL endpoint into a CLI. Use this skill when the user wants to interact with an MCP server, OpenAPI/REST API, or GraphQL API via command line, discover available tools/endpoints, call API operations, or generate a new skill from an API. Triggers include "mcp2cli", "call this MCP server", "use this API", "list tools from", "create a skill for this API", "graphql", or any task involving MCP tool invocation, OpenAPI endpoint calls, or GraphQL queries without writing code.
Use for the CODE half of a managed Intelligence Channel with Slack or Microsoft Teams: customising the Channel a CLI-scaffolded project already ships, or — for a project the CLI did not generate — writing the Channel declaration, the long-running host, and the awaited activation call. Teams provider setup is in scope, because the CLI or dashboard wizard performs it. Creating a Slack app for the first time is not: if no Slack app exists yet, use setup-slack-channel for the provider half and return here for the code.
Optimizes AI skills for activation, clarity, and cross-model reliability. Use when creating or editing skill packs, diagnosing weak skill uptake, reducing regressions, tuning instruction salience, improving examples, shrinking context cost, or setting benchmark/release gates for skills. Trigger terms: skill optimization, activation gap, benchmark skill, with/without skill delta, regression, context budget, prompt salience.
Create, hand off, claim, execute, and close agent tasks through the MemPalace logstream. Use when the user wants to delegate work, prepare a ready-to-paste task for another agent, receive a MemPalace task id, or explicitly launch a supported headless agent in controlled mode.
Agent Script DSL for deterministic Agentforce agents. Trigger when users write or edit .agent files, build FSM-based agents, use the Agent Script CLI (sf agent generate authoring-bundle, sf agent validate authoring-bundle, sf agent preview, sf agent publish authoring-bundle, sf agent activate), or ask about deterministic agent patterns, slot filling, or instruction resolution. Do not trigger for Builder metadata work (use sf-ai-agentforce), agent testing (use sf-ai-agentforce-testing), or persona design (use sf-ai-agentforce-persona).
Find the mistakes agents keep repeating in this repo and make each one impossible. Try architecture first, then types, then a lint whose error names the fix, then a test, and write docs last. Prove each check fails on a real past mistake. Repeat this each time the operator corrects you. Use for /correct.
Source-backed research orchestrator for the Fusion ecosystem. Routes to the correct research agent based on question type. Returns source-backed evidence only; will not invent Framework behavior, component APIs, skill catalog relationships, platform guidance, or backend implementation details. USE FOR: any research question needing source-backed evidence about Fusion Framework APIs, EDS components, the Fusion skill catalog, Fusion platform documentation, or backend service implementation. DO NOT USE FOR: implementing code changes, installing or editing skills, MCP setup or troubleshooting, or inventing Fusion behavior without evidence.
Cold-read the artifact you're focused on from a fresh, zero-context sub-session to confirm it stands on its own — a shower-thought reset for accumulated session bias. Use when a long session has worn away your fresh eyes and you can no longer tell whether the artifact in focus is clear to someone with no prior context; before a handoff, publish, or merge; or when you want a clean-room comprehension smoke test. Spawns a separate context-free reviewer; it diagnoses, it does not fix.
Creates, updates, or optimizes an AGENTS.md file for a repository with minimal, high-signal instructions covering non-discoverable coding conventions, tooling quirks, workflow preferences, and project-specific rules that agents cannot infer from reading the codebase. Use when setting up agent instructions or Claude configuration for a new repository, when an existing AGENTS.md is too long, generic, or stale, when agents repeatedly make avoidable mistakes, or when repository workflows have changed and the agent configuration needs pruning. Applies a discoverability filter—omitting anything Claude can learn from README, code, config, or directory structure—and a quality gate to verify each line remains accurate and operationally significant.
Report local Claude, Codex, Cursor, GitHub Copilot, Grok, Kimi, Z.AI, Alibaba, OpenCode Go, Antigravity, Command Code, MiniMax, MiMo, DeepSeek, OpenRouter, ElevenLabs, Devin, Muse, and Higgsfield quota windows via the quota-axi CLI - remaining effective usable runway, percentages, reset times, cycle-average pace vs the reset clock, a per-scope selection signal, and provider status read from local auth sources, with no routing, no credential minting, and no default ordering preference. Use before deciding whether it is safe to keep spending a provider's quota, when the user asks about usage, rate limits, pace, or remaining quota, or when comparing local provider headroom.
Creates and manages isolated cloud sandboxes (secure code execution environments with dedicated runtimes) on the Daytona platform. Use when a task needs an isolated runtime, sandbox, secure compute, or Daytona SDK/API/CLI operations. Covers Python, TypeScript, Java, Go, and Ruby SDKs
Workflow creation, execution, and template management. Automates complex multi-step processes with agent coordination. Use when: automating processes, creating reusable workflows, orchestrating multi-step tasks. Skip when: simple single-step tasks, ad-hoc operations.
Use for the PROVIDER half of getting a locally running CopilotKit Channels agent to answer in Slack, when no Slack app exists yet — setting up a Channels bot in Slack for the first time, creating the Slack app and its tokens, attaching it to a managed Intelligence Channel, or when a Channel reports setup_required, sits at "Waiting for runtime", the Channel is Online but a Slack mention gets no reply, or a Slack app was built with Socket Mode instead of an Intelligence Request URL. Scoped to an OpenTag checkout, or the OpenTag example inside a channels-sdk clone — the phases assume those conventions (app/channel.tsx, app/env.ts, INTELLIGENCE_CHANNEL_NAME, a local agent on port 8123) and do not describe a project scaffolded by copilotkit init, which already ships its own channel host. If the Slack app and Channel already exist and the question is about declaring or customising the Channel in code, use the copilotkit-channels skill instead.
Guide for creating effective skills that extend agent capabilities with specialized knowledge, workflows, or tool integrations. Use this skill when the user asks to: (1) create a new skill, (2) make a skill, (3) build a skill, (4) set up a skill, (5) initialize a skill, (6) scaffold a skill, (7) update or modify an existing skill, (8) validate a skill, (9) learn about skill structure, (10) understand how skills work, or (11) get guidance on skill design patterns. Trigger on phrases like "create a skill", "new skill", "make a skill", "skill for X", "how do I create a skill", or "help me build a skill".
Use for building, debugging, integrating, migrating, or documenting OpenUI, OpenUI Lang, Agent Interface, OpenUI Cloud, @openuidev packages, streaming generative UI rendering, component libraries, existing-project Cloud integration, self-hosted-to-Cloud migration, migrations from JSON UI formats, Cloud tools (web/image search, artifacts), remote MCP servers, custom function tools and tool loops, and multi-user or multi-app identity (frontend tokens, app_id/user_id, conversation APIs, Responses metadata).
This skill should be used when user wants to access, capture, or reference Claude Code session history. Trigger when user says "capture session", "save session history", or references past/current conversation as a source - whether for saving, extracting, summarizing, or reviewing. This includes any mention of "what we discussed", "today's work", "session history", or when user treats the conversation itself as source material (e.g., "from our conversation").
Provision a zero-config, no-signup, temporary Upstash Redis database for an AI agent with a single POST to https://upstash.com/start-redis, with no account, API key, or SDK setup required. Use when an agent needs scratch Redis right now and the user has not provided credentials, for short-term memory across tool calls, conversation history, a sub-agent work queue, ranked recall, or a quick prototype or demo. Covers idempotent creation and re-fetching credentials, calling the database through the body-style REST API or the official SDKs, and telling the user how to claim it. The database lives 3 days unless the user claims it; not for production data, PII, or secrets.
After you create or change an artifact or skill, taste-test it with our own skills instead of trusting your in-session judgment — recursive self-improvement, made automatic. Use right after writing or editing anything, before calling it done, committing, or handing it off.
Use when creating, refreshing or repairing `.agents/ue-project-context.md`, the project document every other UE skill reads first. Also use when the user says 'project context', 'set up context', 'UE context', 'scan my project', 'onboard the agent to my project', 'update project context', 'configure project', 'what engine version is this project on', 'which plugins do we have enabled', or complains that UE advice keeps coming out generic. For Build.cs and Target.cs mechanics, see ue-module-build-system; for naming and API-macro conventions, see ue-cpp-foundations; for GAS specifics, see ue-gameplay-abilities.
Read the live cycle state and return the single highest-leverage next best action, not a menu. Use when a project is between phases, the author asks what to do next, too many valid threads are open, or the work needs re-entry into frame, build, drive, re0-memo, hate, re0-work, or ship.
Convert an article, tutorial, or prompt pack into focused reusable AgentSkills, one independent capability per skill, with portable instructions, example prompts, working demos, preview screenshots, validation, gallery updates, and a narrow commit. Use when the user asks to turn an article's prompts, tutorial sections, design patterns, interactions, or workflow ideas into complete skills rather than leaving them as prose.
Use when creating or developing, before writing code or implementation plans - refines rough ideas into fully-formed designs through collaborative questioning, alternative exploration, and incremental validation. Don't use during clear 'mechanical' processes
Compare and update the `computedHash` in the root `skills-lock.json` against the latest state of the upstream repository. Skip cloning entries whose `source` does not exactly match `Fandhe-AI/<repo>` (safeguard). Do not touch `skills-lock.json` files inside submodules. Use after merging contribute-skill or syncing upstream, or when asked to "update hashes" or "sync skills-lock".
Generates custom design system rules for the user's codebase. Use when the user says “create design system rules,” “generate rules for my project,” “set up design rules,” “customize design system guidelines,” or wants to establish project-specific conventions for Figma-to-code workflows. Requires Figma MCP server connection.
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Carve guardrail-adjacent items out of scope with safe alternatives before risk-adjacent work starts, then run the safe remainder at full strength in a fresh subagent that only ever sees the carved prompt, never the risky input. Use when a task includes stealth, scraping, privacy, IP, policy, licensing, security, or other safety-adjacent material that could be silently dropped, over-elaborated, or needlessly diluted. Fires on the impulse, not only the topic: the moment you notice yourself about to hedge, soften, silently skip, or brace for a refusal, carve before you execute.
Agentforce Builder metadata path for Builder-managed topics/actions, Prompt Builder templates, GenAiFunction/GenAiPlugin, Models API, and custom Lightning types. TRIGGER when: user maintains or configures Builder metadata agents, creates topics/actions, works with Prompt Builder templates, or touches .genAiFunction, .genAiPlugin, or .genAiPromptTemplate metadata XML files. DO NOT TRIGGER when: Agent Script DSL .agent files (use sf-ai-agentscript), agent testing (use sf-ai-agentforce-testing), or persona design (use sf-ai-agentforce-persona).
Apply a prompt-agnostic execution and verification loop to any substantial task while preserving the original request. Use when the user asks to fan out work, use subagents or independent reviewers, loop until done, benchmark against references, apply a harsh critic, compare candidates blind, improve an existing prompt with verification, or continue until explicit quality gates pass.
Set up Browser Use Cloud payments with x402 — pay per request from a crypto wallet (USDC on Base mainnet), no signup or API key. Two setups it works out up front — "just use it" (set up a wallet so you or Claude Code can run cloud browser tasks paid from the wallet — Claude writes and runs throwaway scripts, nothing touches your codebase) or "build it in" (install the SDK and write the key + code into your project). Walks through wallet setup, funding, .env, and a ~$1 test run. Use when the user asks about x402, pay-per-use, USDC payments, or wants Browser Use Cloud without an API key. For the free-tier signup (reverse-CAPTCHA → API key), use `browser-use cloud signup` or the `cloud` skill instead.
Restart a project or artifact from v0 while preserving only proven lessons, contracts, gates, vocabulary, real-surface tests, and negative corpus. Use when the foundation is wrong, accumulated code is misleading progress, or a new pass should learn from the old one without inheriting its accidental architecture.
USE FOR RAG/LLM grounding. Returns pre-extracted web content (text, tables, code) optimized for LLMs. GET + POST. Adjust max_tokens/count based on complexity. Supports Goggles, local/POI. For AI answers use answers. Recommended for anyone building AI/agentic applications.
Builds with and operates Pi, the minimal terminal coding harness. Use for installing Pi, configuring providers/models/settings/environment variables, creating Pi skills/extensions/packages/themes/prompt templates, embedding Pi through the SDK, integrating over RPC or JSON event streams, parsing sessions, running local models through the llama.cpp router, developing custom Pi providers and TUI components, or using ecosystem packages such as pi-subagents (delegation/orchestration), pi-mcp-adapter (MCP servers), pi-interview (interactive forms), and pi-web-access (web search, fetching, video understanding).
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.