Loading...
Loading...
Found 10,112 Skills
End-to-end GECX/CXAS/CES conversational agent lifecycle -- build agents from requirements (PRD-to-agent), create and run evals (goldens, simulations, tool tests, callback tests), debug failures, and iterate to production quality. Use this skill whenever the user mentions GECX, CXAS, CES, SCRAPI, conversational agents, voice agents, audio agents, agent evals, pushing/pulling/linting agents, or agent instructions/callbacks/tools on the Google Customer Engagement Suite platform.
macOS screen capture, window recording, GIF conversion, and agent evidence bundles from the terminal. Built on ScreenCaptureKit for window-level targeting ffmpeg cannot do. Use when the user wants a screenshot of a specific window or app, a screen recording, a GIF conversion, a before/after diff, an evidence bundle for a PR, OCR text from a window, a terminal VHS recording, a Remotion render, or wants to watch a UI for changes. Requires macOS Screen Recording permission on first run.
Make and receive private payments on Solana via VeilPay. Use when an agent needs to send funds without an on-chain link between sender and recipient, generate shareable payment links, claim incoming payments, perform confidential transfers, or query encrypted balances. Powered by the Umbra ZK shielded pool on Solana mainnet.
Manages Neo4j Aura Agents via the v2beta1 REST API — create, list, get, update, delete, and invoke Aura agents backed by an AuraDB instance. Use when configuring Aura Agent tools (CypherTemplate, SimilaritySearch, Text2Cypher), setting system prompts, deploying agents to REST or MCP endpoints, or invoking agents with natural language queries. Covers OAuth2 auth, organization/project scoping, tool parameter schemas, and InvokeAgentResponse format. Does NOT cover AuraDB instance provisioning — use neo4j-aura-provisioning-skill. Does NOT cover vector index creation — use neo4j-vector-index-skill.
Agent tooling for Motion Canvas — seek, screenshot, scene graph inspection, settings control, and rendering via HTTP API. Requires a browser with the editor open.
Use when starting a session, deciding which framework skill applies to the current task, or sequencing them across a feature. Maps the user's intent to one of the five framework skills (ai-driven-prd, init-claude-project, generate-dev-plan, declarative-design, execute-plan) and enforces the cross-skill operating behaviors. Triggers on "which skill should I use", "where do I start", "how do these skills fit together", "I have a PRD now what", "/using-agent-skills".
Manage GitHub pull request workflows for coding agents. Use when Codex needs to open, update, monitor, or hand off a PR; wait for CI checks or reviewer feedback; inspect unresolved review threads; address requested changes; summarize PR status; or decide whether to continue, wait, report a timeout, or ask for human input.
Search, install, list, remove, update, or scaffold AI agents with the `agentshq` CLI across many coding CLIs and IDEs. Use when the user wants to discover agents, install them into specific clients, or manage an existing agent catalog.
Extract a validated learning from the current session, store it in the central agent learnings file, and sync the resulting Learnings section into the agent definitions used by the supported CLIs. User-only maintenance workflow for durable agent guidance.
Convert a local AGENT.md into a Claude Code optimized agent. Audits one agent against Claude Code runtime behavior, creates a per-agent DAG rewrite plan with source-backed guardrails, and optionally rewrites the frontmatter and system-prompt body so the agent is thinner, more role-specific, and better aligned with Claude's agent runtime. Use when the user says "convert this agent to Claude", "normalize this AGENT.md", "thin this agent", or "rewrite this persona for Claude Code".
Create implementation task plans in `_/local-plans/<plan-name>.md`. First investigate the codebase using the Explore Agent, then document it in verifiable granularity and parallel-executable units, following the standard format (Background & Purpose, Current Status, Design, File Structure Tree, Implementation Steps, Verification Methods) that can be validated by the plan-verifier Agent. Used for requests like "Make a plan", "Design", "Task decomposition", "Think about implementation approach". plan, planning, design, implementation plan, task decomposition, create-plan
前回更新コミット (`_/.last-update-docs` で追跡) からの差分をもとに CLAUDE.md のスキル一覧・リポジトリ構造ツリーを更新する。新スキル追加時、`.claude/agents/` や `.claude/rules/` の変更時、「ドキュメント更新して」「CLAUDE.md を更新して」などで使用。