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 when designing scalable MCP tool routing, dynamic tool retrieval, agent-tool graphs, tool inventory indexing, or routing policies for agents with many available tools.
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安装前可以查看交给 AI 代理的指令内容。
Use this skill when an agent has too many tools to place in context at once, when MCP server inventories change, or when routing errors dominate agent failures.
Treat tool routing as a retrieval system with governance. Do not stuff every tool schema into the prompt. Maintain a synchronized tool index, retrieve candidate tools at runtime, rerank with capability and safety signals, and expose only the smallest useful tool set to the agent.
Build a tool inventory
Create retrieval documents
Route dynamically
Verify before invocation
Measure routing
Use graph routing when tool capabilities are nested under agents, servers, or workflows.
Represent:
Add edges such as owns_tool, requires_scope, works_with, conflicts_with, and handles_domain. Retrieve candidate tools and agents, then traverse the graph to load the final server or specialist agent.
Use tool_inventory_graph.py to audit a JSON MCP inventory and emit a graph-oriented routing report:
python scripts/tool_inventory_graph.py mcp-tools.json
Read routing-patterns.md for implementation patterns and failure modes.
External grounding:
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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)
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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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