Use when designing long-horizon agents that need subagents, isolated context windows, filesystem-backed work, persistence, human approval, MCP tools, or production tracing.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Design long-running agents as a harness with explicit state, bounded delegation, durable artifacts, and reviewable tool calls. Use a higher-level harness when the work needs more than one ReAct loop.
| Need | Pattern |
|---|---|
| Short single-step assistant | Plain tool-calling agent |
| Stateful workflow with branches | LangGraph-style graph |
| Long-horizon work with files and subagents | Deep agent harness |
| Tool execution can affect users or infrastructure | Human-in-the-loop gate |
| Agent needs learned project practices | Durable memory plus context evolution |
Every subagent handoff should include:
DONE, DONE_WITH_CONCERNS, NEEDS_CONTEXT, BLOCKED.See harness-contracts.md for reusable templates.
| Mistake | Fix |
|---|---|
| Letting subagents explore the whole repo | Give exact files, commands, and output contracts |
| Passing huge tool outputs through chat | Store them as artifacts and pass summaries |
| Treating checkpoints as logs only | Resume from checkpoints and test recovery |
| Adding memory without invalidation | Version memory and attach evidence |
| Evaluating only pass/fail | Inspect trajectory quality, retries, dead ends, and repair behavior |
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Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
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Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
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Adds educational comments to a code file so it becomes a learning resource, asking for the file (with a list of close matches) if none is given. Use when preparing code for learners, onboarding, or teaching.
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Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
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Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"
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