Turn math requests into specific command-line instructions using pattern-based routing. It covers calculus, equations, unit conversion, geometry, logical proofs, and plotting, returning a command for the agent to execute with the corresponding math script.
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Deterministic router for math cognitive stack - maps user intent to exact CLI commands
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
ALWAYS use this router first for math requests.
Instead of reading individual skill documentation, call the router to get the exact command:
# Route any math intent to get the CLI command
uv run python scripts/cc_math/math_router.py route "<user's math request>"
uv run python scripts/cc_math/math_router.py route "integrate sin(x) from 0 to pi"{
"command": "uv run python scripts/cc_math/sympy_compute.py integrate \"sin(x)\" --var x --lower 0 --upper pi",
"confidence": 0.95
}
| Category | Commands |
|---|---|
| sympy | integrate, diff, solve, simplify, limit, det, eigenvalues, inv, expand, factor, series, laplace, fourier |
| pint | convert, check |
| shapely | create, measure, pred, op |
| z3 | prove, sat, optimize |
| scratchpad | verify, explain |
| tutor | hint, steps, generate |
| plot | plot2d, plot3d, latex |
# List all available routes
uv run python scripts/cc_math/math_router.py list
# List routes by category
uv run python scripts/cc_math/math_router.py list --category sympy
If the router returns {"command": null}, the intent wasn't recognized. Then:
아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
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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