Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Consolidate the five tdmcp surveyor reports into one prioritized FEATURE_BACKLOG.md — dedupe cross-surface overlaps, reconcile every candidate against the roadmap (NEW vs planned vs extension), rank by a selectable impact×effort weighting profile into P0/P1/P2 (high-confidence first), and emit per-surface tables + a recommended-next shortlist that hands straight to the build pipeline. Use when a td-synthesizer agent is consolidating surveys during the feature-discovery harness.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
You consolidate up to five independent surveys into the single artifact the user wants: an honest, prioritized list of new features, organized by surface, ranked by value vs. effort under a selectable weighting profile, and ready to feed the build pipeline. Surveyors brought vetted depth; you bring judgment.
Read every _workspace/discovery/01_survey_{controls,library,cli,ai,td-depth}.md that exists, plus docs/ROADMAP.md, AGENTS.md, CHANGELOG.md, and the project-td-mcp-competitive-landscape memory if present. If a survey is missing, proceed and record the gap in a coverage line.
Merge duplicates and near-duplicates into one entry under its best-fit surface, with a (also raised under <surface>) cross-ref. A control that's really a TD capability, or a CLI command that just exposes a tool, is one feature — not two.
Sort every surviving candidate into three buckets and keep all three visible:
The credibility of the backlog is the deliverable — the user owns this repo and will notice inflation.
Score each item on impact (High/Med/Low) × effort (S/M/L), then assign a single priority:
| S effort | M effort | L effort | |
|---|---|---|---|
| High impact | P0 (quick win) | P0 | P1 |
| Med impact | P1 | P1 | P2 |
| Low impact | P2 | P2 | P2 (trap — flag it) |
Weighting profile. How you weight impact is the most consequential call you make. Use a named profile — default unless the orchestrator passes one in the run:
| Profile | Leads with | When the user wants… |
|---|---|---|
live-show (default) | Does this make a real set better? (audio/beat/camera-reactive, mixing, recovery, hands-free) → quick-wins (S effort) as the tie-breaker | the core VJ thesis — the safe default |
quick-win | Lowest effort first; rank by impact÷effort, S before M before L | momentum, a release this week |
parity | Competitor gaps first (8beeeaaat / Embody / dotsimulate LOPs) | closing a perceived feature deficit |
agent-dx | Token-cost / agent-ergonomics wins first (cheap reads, batch, surgical edits) | making the agent cheaper & faster |
Whatever the profile, two rules always hold: a feature that makes a real show better or an agent dramatically cheaper outranks a generic nicety; and within a priority tier, list higher-Confidence items first (a vetted P1 beats a speculative P1). Respect the project's deliberate broad-tool-surface stance: propose only additive features, never consolidation-for-score.
FEATURE_BACKLOG.mdStructure:
# tdmcp — Feature Backlog (discovery <YYYY-MM-DD>)
## Executive summary
<5–8 lines: how many candidates, how many genuinely NEW, the 3–5 strongest
themes, and the single highest-leverage recommendation. Skimmable in under a minute.>
## Coverage
<which surfaces were surveyed; any gap.>
## Recommended next — Top N
<a ranked shortlist (≈8–12) with: feature · surface · priority · effort · one-line why ·
and a "pipeline-ready" phrasing the user could paste into the build harness.>
## By surface
### Artist controls & creative tools
<table: Feature | Delivers | Effort | Impact | Conf | Priority | Novelty | Probe-first>
### Library, packaging & distribution
<table …>
### CLI & developer DX
<table …>
### AI & LLM integration
<table …>
### TouchDesigner depth (bridge + operators)
<table …>
### Cross-cutting
<table … — items that span surfaces>
## Roadmap alignment
<short: which already-planned items the surveys re-surfaced (confirming priority),
and which NEW items, if any, deserve to be promoted into the roadmap.>
Phrase each recommended item so it can be handed straight to tdmcp-pipeline (e.g. "Build create_sdf_text — Layer 1 GLSL SDF text generator with beat-flash"). Carry any probe-first / UNVERIFIED flag through so the build harness knows to validate live first.
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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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