Organize agent skills around domain routers that map requests to specific commands. It guides router selection, automatic activation alongside related skills, and the separation between broad activation rules and precise command matching.
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Router-First Architecture
安装前可以查看交给 AI 代理的指令内容。
Route through domain routers before using individual tools. Routers abstract tool selection.
Domain routers (like math-router) provide deterministic mapping from user intent to exact CLI commands. Always use the router first; only bypass for edge cases.
math-router route "<intent>" before any math operationcoActivate in skill-rules.json)command: nullDomain skills should co-activate with their router:
{
"math/abstract-algebra/groups": {
"coActivate": ["math-router"],
"coActivateMode": "always"
}
}
This ensures the router is always available when domain knowledge is activated.
Keep the trigger layer broader than routing - the router should handle "not found" gracefully.
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Coordinate background agents through saved files, keeping lengthy work transcripts out of the main conversation. It defines how to pass results between agents, monitor progress, and verify completed work with tests.
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Delegate implementation, file reading, and testing to separate agents, then bring concise summaries back to the main conversation. The rules explain when delegation helps and when a small edit is better handled directly.
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Organize implementation work across research, planning, validation, implementation, and review agents. Each stage passes files to the next, while implementation starts with failing tests and the main conversation coordinates the workflow.
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Connect Agentica SDK agents to Claude Code CLI through a proxy, an intermediary server. Use setup and debugging guidance to address file permissions, streamed responses, result formatting, and agents reporting success without performing the requested operations.
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Consult Agentica APIs when building workflows where multiple AI agents cooperate. This reference covers eleven coordination patterns, agent tracking, shared state, handoffs, and ways to combine results, with pointers to detailed API specifications.
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Write clearer instructions for Agentica and REPL agents by specifying roles, file operations, and output formats. Includes templates for dividing research, coordinating specialists, reviewing solutions, and passing results between agents through files.
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