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Found 178 Skills
Reference for writing and editing skills well — the vocabulary and principles that make a skill predictable.
Build production-ready AI workflows using Firebase Genkit. Use when creating flows, tool-calling agents, RAG pipelines, multi-agent systems, or deploying AI to Firebase/Cloud Run. Supports TypeScript, Go, and Python with Gemini, OpenAI, Anthropic, Ollama, and Vertex AI plugins.
JEO — 통합 AI 에이전트 오케스트레이션 스킬. ralph+plannotator로 계획 수립, team/bmad로 실행, agent-browser로 브라우저 동작 검증, 작업 완료 후 worktree 자동 정리. Claude, Codex, Gemini CLI, OpenCode 모두 지원. 설치: ralph, omc, omx, ohmg, bmad, plannotator, agent-browser.
Ultimate multi-agent framework for Google Antigravity. Orchestrates specialized domain agents (PM, Frontend, Backend, Mobile, QA, Debug) via Serena Memory.
oh-my-claudecode — Teams-first multi-agent orchestration layer for Claude Code. 32 specialized agents, smart model routing, persistent execution loops, and real-time HUD visibility. Zero learning curve.
Discover and install related skills from inference.sh skill registry. Helps find complementary skills for your AI workflow. Use for: skill discovery, workflow expansion, capability exploration. Triggers: related skills, find skills, skill discovery, complementary skills, expand workflow, more capabilities, similar skills, skill suggestions
Build multi-step AI content creation pipelines combining image, video, audio, and text. Workflow examples: generate image -> animate -> add voiceover -> merge with music. Tools: FLUX, Veo, Kokoro TTS, OmniHuman, media merger, upscaling. Use for: YouTube videos, social media content, marketing materials, automated content. Triggers: content pipeline, ai workflow, content creation, multi-step ai, content automation, ai video workflow, generate and edit, ai content factory, automated content creation, ai production pipeline, media pipeline, content at scale
Run a second round on a contested question by circulating each subagent's independent proposal to the other authors and asking for structured pros and cons, then synthesize. Use this skill whenever you have multiple independent proposals or opinions on a contested decision — architecture tradeoffs, code review disagreements, design choices, competing root-cause theories — and want sharper analysis than you'd produce by synthesizing alone. Pairs naturally with the council and research skills; reach for it liberally whenever proposals diverge.
Build strong Codex Goals from rough user objectives. Use when the user asks to create, write, generate, improve, expand, or refine a Codex `/goal`; mentions Codex Goals, goal mode, persistent objectives, "持续执行", "扩充目标", "生成 goal", "keep working until", or wants Codex to ask clarifying questions before starting a long-running objective. Helps draft evidence-based goal text and may start a goal only after explicit user approval.
Use when running Claude Fable on codebase-heavy or token-heavy work and the user wants Fable to orchestrate research, coding, and testing while cheaper subagents do bounded heavy lifting.
Update ElevenLabs agent skills from a merged weekly changelog in elevenlabs-dx, then open a pull request in elevenlabs/skills. Trigger after a changelog merges to main on elevenlabs-dx, or when asked to update skills from changelog YYYY-MM-DD.
Populate `<docs-dir>/features/<slug>.md` for one, several, or every undocumented feature area by dispatching up to 10 parallel subagents — one per feature. The agent docs directory is discovered from `AGENTS.md` — typically `agents-docs/` (the `setup-agentic-repository` default) but may be elsewhere if `--docs-dir` was used. Use whenever the user wants to document features, fill out feature docs, write up specific features (e.g. "document auth and billing"), document all undocumented features, or follow up on `find-features` discovery. This is the natural sequel to `find-features` — that skill identifies what is missing, this skill writes the docs in parallel.