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Found 6,510 Skills
Delegate a sub-task to Claude Code via the Agent Client Protocol (ACP). Use this skill whenever you want to hand off work to Claude — complex agentic coding with MCP tool access, detailed multi-file refactors, tasks requiring Claude's reasoning style, or anything where Claude's strengths give an advantage. Also invoke when the user asks you to "ask Claude", "use Claude for this", or "run this through Claude". The script handles subprocess lifecycle and ACP session setup; you just provide the prompt and read stdout.
Apex test execution, coverage analysis, and test-fix loops with 120-point scoring. Use when the user needs to run Apex tests, check code coverage, fix failing tests, or work with *Test.cls / *_Test.cls files. TRIGGER when: user runs Apex tests, checks code coverage, fixes failing tests, or touches *Test.cls / *_Test.cls files. DO NOT TRIGGER when: writing Apex production code (use generating-apex), Agentforce agent testing (use testing-agentforce), or Jest/LWC tests (use generating-lwc-components).
Controls a running iOS, iPad, or Apple Watch Simulator via the serve-sim CLI (npx serve-sim) and streams it into the host agent's preview pane. Use whenever the user wants an AI agent to view or drive an Apple Simulator — streaming to preview, taps at normalized coordinates, multi-touch gestures, hardware buttons, rotation, memory warnings, CoreAnimation debug, synthetic camera injection, media drag-drop, or managing app privacy permissions. Triggers include "serve-sim", "iOS simulator", "Apple simulator", "iPad simulator", "Apple Watch simulator", "stream the simulator", "show the simulator in preview", "view the simulator here", "open simulator in preview", "simulator gestures", "tap on the simulator", "rotate the simulator", "inject camera feed", "grant simulator permissions", "allow push notifications in the simulator", or any request to drive or display an Apple Simulator visually. Do NOT use for Android emulators, building/installing an iOS app (use xcodebuild), booting a simulator from scratch (use xcrun simctl boot), in-app React Native runtime debugging (use rn-debugger), or real iOS hardware.
Run an Anthropic Claude Managed Agent — a cloud agent harness (container + filesystem + tools), the cloud counterpart of the local wasm-agent runtime
AI agent skill for CompressO — a free, open-source, offline desktop tool for batch video and image compression built with Tauri + React. Use when the user needs to compress, trim, convert, or embed subtitles into video/image files locally without any network dependency. Covers installation (Homebrew, DMG, MSI, AppImage, DEB), build from source (Rust + Node.js + pnpm), and guidance on FFmpeg/pngquant/jpegoptim/gifski pipelines. Triggers on: compresso, compress video, compress image, batch compression, ffmpeg compression, tauri desktop compression, offline video compress.
Guides CI/CD for agent skills repositories and skill packages—pipeline design (build, test, validate, package), GitHub Actions for PR checks and release promotion, environment gates, secrets hygiene (no secrets in repo), skill-creator integration (quick_validate.py, package_skill.py), .skill artifact strategy, rollback, and operational runbooks for skill releases. Use when the user mentions CI/CD, CI/CD engineer, pipeline design, GitHub Actions, skill validation CI, package skills, release pipeline, deploy skills, PR checks, continuous integration, or skill release workflow—not application-only CI without skill packaging (devops), pre-flight plan go/no-go (build-validator), IDP or golden paths (platform-engineer), org-wide SLO and error-budget programs without pipeline ownership (site-reliability-engineer), or portfolio catalog governance without pipeline YAML (ai-skill-manager).
Improve Coval trace quality after basic ingestion works. Use when traces are sparse, missing useful STT/LLM/TTS/tool spans, missing attributes needed for Coval built-in metrics, or when a customer wants maximum debugging and observability value from agent traces.
Connects NemoClaw to a local inference server. Use when setting up Ollama, vLLM, TensorRT-LLM, NIM, or any OpenAI-compatible local model server with NemoClaw. Trigger keywords - nemoclaw local inference, ollama nemoclaw, vllm nemoclaw, local model server, openai compatible endpoint, switch nemoclaw inference model, change inference runtime, nemoclaw additional model, nemoclaw sub-agent model, openclaw sub-agent, agents.list, sessions_spawn, vlm-demo, nemoclaw tool calling, ollama tool calls, vllm tool-call-parser, raw json in tui, nemoclaw inference options, nemoclaw onboarding providers, nemoclaw inference routing.
Use this when users want to set up daily automated promotion and marketing for their Claude Code skills — this includes researching how top skills are promoted on marketplaces (ClawHub / openclaw / SkillsMP / agentskills.io), generating a skill-specific marketing plan, auto-posting to X (Twitter) via xurl, and drafting community discussion posts (Reddit / HN / Discord). Triggers: "推广 skills", "营销 skills", "自动发推广", "每天自动推广", "skill marketing", "promote my skills", "/wjs-promoting-skills".
Drive terminal sessions, panes, and TUIs from an agent — spawn shells, send keystrokes, snapshot pixel-perfect PNGs of any pane, and extend shux itself with line-delimited JSON-RPC plugins in any language. Use when you need to multiplex terminal work, drive a TUI you'd otherwise control with tmux / screen / iTerm2 / expect / pexpect / asciinema / vhs / termshot, run scripted CLI/REPL interactions, do headless visual regression on a terminal UI, or write a process plugin that subscribes to the shux event bus and calls back through `window.rename`, `pane.send_keys`, `state.apply`, etc. Trigger phrases include "drive terminal", "spawn pty session", "send keys to a TUI", "screenshot a tui", "snapshot pane", "replace tmux", "iTerm2 automation", "expect script", "headless terminal test", "agent multiplexer", "asciinema record", "write a shux plugin", "extend shux", "shux plugin install".
Chinese Git Commit Skill. Analyze changes and generate Chinese conventional commit messages. Triggered when the user says "submit", "commit", "submit code", "submit changes", or "/commit-zh". Executed entirely by the main agent, no subagents used.
Context layer for data agents - builds semantic layer, wiki, and warehouse metadata to enable accurate AI-powered analytics queries