Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Design a tdmcp feature into an implementable spec before any code is written — choose the layer, define the Zod input schema, lay out the TD network topology, plan the bridge/Python approach, sketch a UI wireframe when relevant, and list probe-first risks + the test plan. Use whenever a tdmcp feature idea needs a design/wireframe/spec, or when someone asks to plan/scope/architect a new tool, generator, effect, control, or AI prompt for the TouchDesigner MCP server.
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实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
A spec is good when a builder can implement it in one file + one test without re-deciding anything. Aim for that bar.
docs/ROADMAP.md (the idea is usually already scoped there), AGENTS.md (the conventions), and 1–2 neighbour tools in the target src/tools/layer*/ for the exact file pattern.src/tools/layer1/) — an artist tool that builds a whole wired+arranged network (goes through orchestration.ts).src/tools/layer2/) — a building block (connect, control panel, animate, external IO).src/tools/layer3/) — atomic node CRUD / inspection / raw-Python escape hatch.src/tools/vault/ — Obsidian-vault bridge. A src/prompts/ entry — when the value is guidance to the model, not a deterministic build (multimodal / natural-language / critique ship as prompts).src/tools/layer<N>/<camelCaseName>.ts.bind_to_channel, reusing the shipped binding path instead of inventing one. Verify every operator type against the KB (tdmcp://operators/… or search_operators) — never invent a type.buildPayloadScript (__PAYLOAD_B64__) executed through the client and parsed with parsePythonReport. Propose a new REST endpoint only when streaming or performance genuinely demands it.layer*/index.ts, src/cli/agent.ts command name + flags, docs regenerate automatically).One file per feature at _workspace/01_design_<feature>.md with these sections in order: Summary · Layer + target path · Input schema (param table) · Network topology · Bridge/Python approach · UI wireframe (if any) · Probe-first risks · Test plan · Integration notes.
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Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Use when a hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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Reference for how BDB structures autonomous software engineering work — the seven-node dispatcher graph (Architect, TechLead, UI/UX, Engineering, Media/EventTech, Reviewer, Shipping) that /startcycle-graph actually runs. Use when you need the high-level lifecycle framing without inventing your own process.
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Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling.
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Harness patterns for coding agents — memory, permissions, context engineering, delegation, skills, hooks, bootstrap.
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agenttrail: live map of a multi-agent build in the browser: which plan component is being worked on, by which agent or harness, what is done and what is stuck. Use when a multi-agent pipeline starts (/startcycle, /startcycle-graph, /teamwork-preview) or after a plan-canvas approve, when the user asks to see what the agents are doing ("live map", "build board", "who is running now"), or by yourself whenever a multi-agent run is under way — no user prompt needed.
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