Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Survey the whole tdmcp project and produce a prioritized list of NEW features it could implement — across artist controls, CLI/DX, AI/LLM integration, and TouchDesigner depth. Use whenever the user wants to brainstorm, discover, survey, list, or audit what features/tools/effects/controls/commands/prompts/capabilities tdmcp *could* add, asks 'what could we build / what's missing / what are the opportunities / ideas for the project', or wants a feature backlog or gap analysis. Also for follow-ups: re-run, refresh, update, re-survey, deepen, or re-prioritize the backlog, or survey just one surface (e.g. 'CLI ideas only'). This is the IDEATION harness — it produces a list to decide from; it does NOT build. When the user has already chosen a feature and wants it implemented/shipped/added, use tdmcp-pipeline instead.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Coordinate a fan-out of surveyors + one synthesizer to produce a single prioritized feature backlog for tdmcp, deduped and reconciled against the roadmap. This harness finds and ranks ideas; the tdmcp-pipeline harness builds the chosen ones. Keep the boundary crisp: discovery answers "what should we consider next?", pipeline answers "build this."
| Stage | Mode | Why |
|---|---|---|
| Survey | sub-agent (fan-out, parallel) | the five surveyors are fully isolated — each owns one surface, no inter-comms needed; the textbook fan-out case (mirrors the pipeline's design/build stages) |
| Synthesize | sub-agent (×1) | a single reasoning-heavy consolidation pass over result files — no producer↔reviewer loop, so no team needed |
No TeamCreate here — surveys are pure result-passing via files, so sub-agents are the right tool over team overhead. All Agent calls use model: "opus".
| Agent | Type | Skill | Output |
|---|---|---|---|
td-surveyor (×up to 5) | custom | td-feature-survey | _workspace/discovery/01_survey_<surface>.md |
td-synthesizer | custom | td-feature-synthesize | _workspace/discovery/FEATURE_BACKLOG.md |
The five surfaces: controls (Layer 1/2 creation & performance), library (vault + recipes + .tox/component packaging + distribution), cli (CLI/DX), ai (prompts + local-LLM copilot), td-depth (Layer 3 + bridge + operator KB).
_workspace/discovery/ exists._workspace/discovery/ → fresh run. Go to Phase 1._workspace/discovery_<YYYYMMDD_HHMMSS>/, then Phase 1.live-show; if the user signals otherwise ("favour quick wins", "what closes competitor gaps", "make the agent cheaper"), pass quick-win / parity / agent-dx to the synthesizer in Phase 3._workspace/discovery/.Spawn one td-surveyor per in-scope surface in a single message (subagent_type: "td-surveyor", model: "opus"). Each prompt states its surface assignment (controls / library / cli / ai / td-depth), the hard rule stay inside your surface; write _workspace/discovery/01_survey_<surface>.md incrementally, and asks for a short summary return (counts + headline ideas) so the leader's context stays lean.
Resilience (transient errors are common at this fan-out width). When the batch returns, verify by file, not by return value: check that each in-scope 01_survey_<surface>.md exists and looks complete (has a tally). For any surface whose agent returned a socket/API error or left a missing/truncated file, re-spawn just that one surveyor once before synthesis — the incremental writes mean a retry resumes cheaply. If a surface still fails after one retry, proceed without it and record the gap (the synthesizer notes coverage). Do not block the whole run on one surface.
Spawn one td-synthesizer (model: "opus"), telling it the weighting profile from Phase 1 (default live-show). It reads every 01_survey_*.md, plus docs/ROADMAP.md / AGENTS.md / CHANGELOG.md / competitive memory, dedupes, reconciles against the roadmap, prioritizes under that profile (high-confidence first within each tier), and writes _workspace/discovery/FEATURE_BACKLOG.md. It returns a self-contained prose summary.
Single-surface shortcut: if only one surface was in scope, you may skip the synthesizer and relay that survey directly — but still run it through synthesis if the user wants priority/roadmap reconciliation.
_workspace/discovery/FEATURE_BACKLOG.md.tdmcp-pipeline build harness._workspace/discovery/ for audit.[leader] ──scope──▶ td-surveyor ×5 (parallel, one message)
controls │ library │ cli │ ai │ td-depth
└── each writes _workspace/discovery/01_survey_<surface>.md ──┐
(leader retries any that errored, once) ▼
td-synthesizer (reads 5 + roadmap, weighting profile)
│
_workspace/discovery/FEATURE_BACKLOG.md
│
summary relayed ──▶ user ──▶ (optional) tdmcp-pipeline
| Situation | Strategy |
|---|---|
| One surveyor returns thin/empty | Keep its (small) report; synthesizer notes the lean surface. Don't block the batch. |
| One surveyor returns a socket/API error or a missing/truncated file | Re-spawn just that one surveyor once (incremental writes make the retry cheap). Only if it fails again, synthesize from the surveys that landed and name the uncovered surface in the coverage line. |
| Surveyor cites an unconfirmed operator | Idea is kept with UNVERIFIED — probe live; the flag rides through into the backlog so the build pipeline validates first. |
| Two surveys overlap on the same idea | Synthesizer merges into one entry under the best-fit surface with a cross-ref; not an error. |
| User scoped to one surface | Spawn only that surveyor; skip or keep synthesis per whether they want prioritization. |
_workspace/discovery/ already exists | Phase 0 decides partial-refresh vs. new-run; never silently overwrite a prior backlog. |
Normal: user asks "what new features could we add?" → Phase 1 sets scope = all five, profile = live-show → 5 td-surveyor fan out in one message, each writing its 01_survey_*.md incrementally → leader verifies all five files landed (re-spawns any that errored, once) → td-synthesizer merges, dedupes against ROADMAP Phase 13 / deferred-v0.6.0+, ranks into P0/P1/P2 (high-confidence first), writes FEATURE_BACKLOG.md → leader relays the executive summary + Top-N shortlist and offers to feed picks into tdmcp-pipeline.
Error / scoped: user asks "just give me CLI feature ideas" → scope = cli only → one td-surveyor runs → synthesizer (or direct relay) reconciles the CLI candidates against the roadmap and reports; the other three surfaces are explicitly out of scope, noted in the coverage line.
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.
Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when a hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Harness patterns for coding agents — memory, permissions, context engineering, delegation, skills, hooks, bootstrap.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.