- 📁 references/
- 📄 .gitignore
- 📄 README.md
- 📄 README_EN.md
Production-grade Agent development methodology extracted from Claude Code. 7-dimension framework covering tool design, system prompts, permission & safety, multi-agent orchestration, token economy, memory/state, and extensibility. Supports architecture design, implementation guidance, and agent review. Trigger on "Agent design", "build an agent", "AI agent", "tool design", "system prompt architecture", "agent review", "multi-agent", or any agent development concern.
Set up evals for an agent codebase or check eval status after changes. Determines readiness, identifies what can be tested, and prepares the environment. Use when starting evals for the first time, returning after a code change, or figuring out what to do next. Also triggered by "set up evals", "is my agent ready?", "eval status", "what should I do next?", "init eval", "evaluate my agent", "test my agent", "help me eval this", "get started with evals", "where do I start", "how do I test this agent", "check my setup". This is the default entry point, use it whenever a user wants to evaluate an agent and you're unsure which skill to start with.
Create or update agent prompt overrides for worca pipeline agents. Use when the user wants to customize agent behavior per-project, add project-specific rules, replace agent sections, or modify how planner/coordinator/implementer/tester/guardian agents work. Triggers on "override agent", "customize agent", "agent override", "change implementer rules", etc.
Spawns AI coding agents in isolated git worktrees. Use when the user asks to spawn or launch an agent, delegate a task to a separate agent, work in a separate worktree, or parallelize development across features.
AI agent orchestrator — manage teams of AI agents that work on your codebase in parallel. Use when the user wants to: run multiple agents, coordinate AI work, deploy agent teams, manage tasks/goals/agents, check orchestrator status, or mentions 'orch', 'orchestry', 'agents team', 'agent orchestration'.
- 📁 references/
- 📁 scripts/
- 📄 SKILL.md
Run agent definitions as sub-agents. Use when the user names an agent or sub-agent to run, references an agent definition, or delegates a task to an agent.
This skill should be used when the user asks about agent architecture, evaluation, metrics, production monitoring, debugging agents, or best practices for building reliable AI agents. Use for questions like "evaluate my agent", "set up production monitoring", "add guardrails", "detect hallucinations", "agent anti-patterns", "compare experiments", "create evaluation dataset".
Create and configure A2A Agent Cards — the discovery document describing an agent's capabilities, skills, authentication, and endpoint. Use when defining what your agent exposes to other agents.
- 📁 .agents/
- 📁 .github/
- 📁 docs/
- 📄 .gitattributes
- 📄 .gitignore
- 📄 CHANGELOG.md
> AI Agent 专用的 BOSS 直聘求职 CLI 工具 — 搜索、筛选、打招呼、沟通管理全流程自动化。
- 📁 examples/
- 📁 references/
- 📁 scripts/
- 📄 SKILL.md
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", "disallowedTools", "block tools", "agent denylist", "maxTurns", "agent memory", "mcpServers in agent", "agent hooks", "background agent", "resume agent", "agent teams", "permission rules", "permission mode", "delegate mode", "agent team", "team lead", "teammate", "multi-agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
- 📁 references/
- 📁 scripts/
- 📄 SKILL.md
Curious Agent 接入工具包。When an agent needs to check its knowledge confidence on a topic, trigger active exploration, sync discoveries, or share new findings with the user. Covers: (1) confidence checking before answering, (2) injecting topics for exploration, (3) syncing exploration results to memory, (4) proactive sharing of new discoveries. Trigger scenarios: user asks a question, agent wants to check its knowledge boundary, agent wants to explore a topic proactively.
This skill should be used when the user asks to "create agent", "build agent", "new agent", "add agent", "에이전트 만들어줘", "에이전트 추가해줘", "서브에이전트 추가", or when the orchestrator detects no suitable agent exists for a task.
