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Found 3,444 Skills
Firecrawl produces cleaner markdown than WebFetch, handles JavaScript-heavy pages, and avoids content truncation. This skill should be used when fetching URLs, scraping web pages, converting URLs to markdown, extracting web content, searching the web, crawling sites, mapping URLs, LLM-powered extraction, autonomous data gathering with the Agent API, or fetching AI-generated documentation for GitHub repos via DeepWiki. Provides complete coverage of Firecrawl v2.8.0 API endpoints including parallel agents, spark-1-fast model, and sitemap-only crawling.
Convert structured UX specs and product context into a sequenced prompts.md file for Claude Code. Use when a user has completed upstream design thinking (problem framing, PRD, UX spec) and needs to translate that into step-by-step prompts that coding agents can execute incrementally. This skill bridges design artifacts to code generation.
Use when an approved current phase has 3 or more independent ready tasks and parallel execution will materially reduce cycle time. Orchestrates bounded workers, monitors blockers and file conflicts, coordinates rescues, and hands off to planning or reviewing when the current execution scope is complete. Use for prompts about swarming, parallel workers, launching multiple agents, coordinating a worker pool, or running approved current-phase work at scale.
Use when creating a new beo skill, editing an existing beo skill, or pressure-testing a beo skill before deployment. This skill should win whenever the task is to make a beo skill robust against rationalization, misuse, or failure under pressure. Do not use it for project-specific AGENTS.md conventions, one-off solutions, or ordinary feature planning.
Audit the active repo, MCP servers, plugins, connectors, env surfaces, and harness setup, then recommend the highest-value ECC-native skills, hooks, agents, and operator workflows. Use when the user wants help setting up Claude Code or understanding what capabilities are actually available in their environment.
Better Harness Tools for Claude Code — a Python (and in-progress Rust) rewrite of the Claude Code agent harness, with CLI tooling for manifest inspection, parity auditing, and tool/command inventory.
Triage GitHub issues through a label-based state machine with interactive grilling sessions. Use when user wants to triage issues, review incoming bugs or feature requests, prepare issues for an AFK agent, or manage issue workflow.
Connect Codex CLI as an MCP server — giving you codex_run and codex_review as native tool calls instead of black-box bash commands. codex_run covers six modes: explore (broad codebase discovery), inspect (targeted read-only and injected-context follow-up), build (write/edit code), debug (reproduce→diagnose→fix→verify), test (write/run tests), research (web search only). codex_review runs independent code review in an isolated thread. Each mode bakes in task-specific instructions so Codex performs well per task type. Use this skill whenever the user mentions: "set up codex MCP", "connect codex to claude", "codex MCP server", "install codex tools", "configure codex integration", or wants Codex available as native tools in any agent. Distributed via `npx skills add` — no global install needed.
OpenClaw Task Protocol Worker skill. Access the OpenClaw distributed task network, automatically poll for available tasks, claim, execute and submit results. Trigger keywords:「claim task」「view task」「access task network」「openclaw task」「task protocol」「be a lobster」「do task」 When to use: (1) Agent needs to access the OpenClaw task network to claim and complete tasks, (2) User requests to view/claim/submit tasks, (3) User wants to create tasks as a publisher for other lobsters to complete, (4) Any operations involving the OpenClaw distributed content publishing protocol.
Guide for creating properly structured YAML configuration files for MassGen. This skill should be used when agents need to create new configs for examples, case studies, testing, or demonstrating features.
Invoke MassGen's multi-agent system. Use when the user wants multiple AI agents on a task: writing, code, review, planning, specs, research, design, or any task where parallel iteration beats working alone.
Use Tabbit with agent-browser by reading Tabbit's live DevToolsActivePort file, deriving the browser wsEndpoint, and routing browser actions through agent-browser --cdp.