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Authoritative reference for submitting tdmcp to the Anthropic Connectors Directory as a Claude Desktop Extension (MCPB). Use whenever drafting, checking, or fixing the submission — it defines the two submission paths, why tdmcp is a Desktop Extension (never a remote connector), every form field, the rejection-causing gates, and the local-only compliance story. Read this before writing any submission deliverable.

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How to migrate the tdmcp Claude Desktop bundle from legacy .dxt to .mcpb (MCP Bundle) and keep it building — covers the manifest schema (verify against the installed packer, never hardcode), the build-mcpb.mjs packer/zip-fallback flow, the npm scripts, and the full .dxt→.mcpb reference sweep across docs and scripts. Use when packaging or migrating the tdmcp desktop bundle.

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Design the MixerSceneIntent, approval state, JSON schema, CLI examples, audit entries, and tests for AI-Controlled Party mixer/Soundcraft Ui24R scene arming. Use whenever a task mentions mixer scenes, Ui24R snapshots/cues, operator-approved mixer control, show-director contract updates, schema updates, dry-run CLI shape, or follow-ups that revise this contract.

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Design the Soundcraft Ui24R adapter boundary for AI-Controlled Party: dry-run, Bitfocus Companion, direct Node bridge, connection health, config, failure handling, and live-validation gates. Use whenever a task mentions Soundcraft, Ui24R, snapshots, cues, Companion, soundcraft-ui-connection, mixer bridge, or revising the adapter design.

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Implement ONE tdmcp tool from a spec — the canonical file pattern (Zod schema + …Impl + register… ToolRegistrar), a bridge Python payload via buildPayloadScript, and an offline msw unit test — touching only new files, never shared registries. Use when coding/implementing/writing a tdmcp tool, generator, effect, control, CHOP/TOP/SOP builder, or Python bridge work, especially when several features are built in parallel.

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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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Orchestrates the AI-Controlled Party mixer/Soundcraft Ui24R design team. Use whenever the user wants to design, update, refine, re-run, or implement-plan the Soundcraft Ui24R scene-arming expansion, mixer-aware AI party, operator-approved mixer cues, snapshots/cues/show control, Companion bridge, or any follow-up based on prior mixer design results. Produces a spec for tdmcp-pipeline; does not implement runtime code.

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Drive a whole tdmcp feature BACKLOG to completion as resumable, wave-by-wave releases — the campaign layer ABOVE tdmcp-pipeline/tdmcp-feature-lead. Use whenever the user wants to implement an ENTIRE backlog or discovery file (e.g. _workspace/discovery*/FEATURE_BACKLOG*.md), 'all the features', many features across multiple releases, or a long autonomous build campaign, AND for every follow-up: continue/resume the campaign, run the next wave, re-run a failed wave, fold in QA results, or check campaign status. Backed by a ledger.json so re-running is idempotent (skips shipped work, resumes interrupted work) and resilient (retry-once then quarantine-and-continue). For a SINGLE feature or one small batch, use tdmcp-pipeline instead; this skill is for the whole ledger.

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Adds new visual examples to the tdmcp prompt cookbook documentation — both the English and Portuguese versions. Use when asked to: add more cookbook examples, create visual examples for the docs, show more surprising things you can do, add entries to the prompt cookbook, expand the cookbook, or any request to extend the cookbook with new prompts and results. Runs a 3-phase pipeline: curate candidates → write EN → write PT.

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Restructure and enrich the tdmcp documentation site for artists — categorized/collapsible sidebar (EN+PT), interactive goal-based guide home, new step-by-step tutorials, copy-prompt/level-badge components. Use whenever the user asks to make the docs more interactive, easier to navigate, better organized, add categories/subcategories, add tutorials, improve docs UX/IA, or for follow-ups: re-run, continue, fix QA findings, add one more tutorial, re-organize a section, or update the docs structure. NOT for syncing docs with a release (tdmcp-docs-roadmap-update) or cookbook entries (tdmcp-cookbook-examples).

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Updates tdmcp docs and roadmap for newly shipped or newly merged capabilities. Use when asked to update docs, update the roadmap, reconcile release docs, document new features, sync docs with CHANGELOG/package release, refresh cookbook examples after a feature wave, re-run/continue/fix a docs-roadmap pass, or check whether docs/ROADMAP.md is current. Runs a sub-agent workflow: release audit -> roadmap/docs edit + cookbook sync -> QA.

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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.

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Scout the TouchDesigner community for what's HYPED right now — community showcases, recent tutorials, generative-AI bridges, hardware interaction trends, visual-aesthetic trends of 2025-2026 — then propose tdmcp tools that ride those trends AND are easy to build. Use whenever the user wants to brainstorm new feature ideas based on what's trending in TouchDesigner, asks for 'hype' or 'trending' features, asks 'what are people doing in TD right now / what's hot / what's hype', wants tools inspired by community trends, asks to scout TD trends/aesthetics/integrations, or says things like 'ideias hype', 'novas ideias', 'o que está em alta', 'criar ferramentas para o que está bombando', 'tendências do TouchDesigner'. Also for follow-ups: refresh, rescout one surface, re-rank under another profile, deepen a trend, or filter for buildable-easy items. This is an EXTERNAL trend ideation harness — complementary to tdmcp-feature-discovery (which is INTERNAL gap analysis). It produces `_workspace/hype-scout/HYPE_TOOL_BACKLOG.md` ranked by Hype × Build-Ease; it does NOT build. Once a feature is chosen from the backlog, hand it to tdmcp-pipeline.

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Study a merged or shipped tdmcp implementation and extract reusable learnings: code improvements, runtime/UX lessons, test gaps, docs updates, roadmap items, and harness changes. Use when the user asks to learn from a completed feature/project/PR/build, analyze what can be improved from an implementation, or turn a real installation experience into actionable tdmcp improvements. This is a post-implementation learning harness; it does not replace tdmcp-pipeline for building or tdmcp-quality-audit for broad repo audits.

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Orchestrates the dedicated Kinect wall harp implementation team. Use whenever the user asks to build, implement, continue, fix, QA, document, or ship the Kinect wall harp, Kinect v2 wall-depth harp, FreenectTD depth-blob hand tracking, projected wall strings, pluck synth harp, or this feature's Layer 1 tool/recipe/docs. Use this before the generic tdmcp-pipeline for this feature.

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Plan and implement native RayTK (t3kt/raytk) raymarching/SDF toolkit integration into tdmcp — beyond the existing package-manager staging, into AI-driven RayTK operator (ROP) node graphs. Use whenever the user wants to build, plan, design, implement, continue, fix, QA, or ship RayTK support: create/wire RayTK ROPs, a RayTK operator knowledge catalog, a RayTK-native raymarch/SDF scene tool, RayTK recipes, or the RayTK setup/doctor flow — including follow-ups (re-run, continue, refresh after a new RayTK release, re-QA, docs). Also triggers on 'raytk', 'raymarching toolkit', 'SDF toolkit', 't3kt', 'montar um build para o raytk', 'integrar o raytk'. This owns RayTK integration specifically; use it before the generic tdmcp-pipeline for this feature. Simple questions about RayTK can be answered directly.

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Drive the ENTIRE tdmcp roadmap-to-1.0 to completion as a resumable, wave-by-wave campaign — Milestone 4 (generative-AI bridge wave), Milestone 5 (mixer scene arming), and the v1.0 consolidation gates G1–G6 — routing each class of work to the right existing sub-harness. Use whenever the user wants to "implement everything / all the milestones / the whole roadmap / finish the road to 1.0", run the next milestone, close the consolidation gates, or build a long autonomous campaign across M4/M5/G1–G6. ALSO use for every follow-up: continue/resume the roadmap campaign, run the next wave, re-run a failed wave, fold in QA results, check campaign status, re-prioritize, or scope to one milestone/gate. This is the CAMPAIGN layer ABOVE tdmcp-pipeline / tdmcp-feature-lead / tdmcp-backlog-campaign — it sequences across MULTIPLE sub-harnesses (tools, mixer, coverage, docs, bridge, recipes, submission), which the generic backlog-campaign does not. For a SINGLE feature use tdmcp-pipeline; for one tool-shaped backlog file use tdmcp-backlog-campaign. Simple questions can be answered directly.

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Orchestrate any tdmcp test-coverage work: run the coverage harness, inspect coverage gaps, plan focused Vitest/msw or bridge tests, delegate coverage writers, verify coverage deltas, and re-run gates. Use whenever the user asks to raise coverage, add broad regression coverage, create a test harness, improve tests, re-run a coverage wave, or fix a coverage gate.

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How to author one new tdmcp MCP tool the house way — the file shape (XImpl + registerX), the Python-bridge pattern (buildPayloadScript/parsePythonReport over executePythonScript), the result helpers (errorResult/guardTd/jsonResult/structuredResult), fail-forward error handling, ESM/.js + Biome style, and the offline msw unit test that proves it. Load this whenever building, extending, reviewing, or testing a tdmcp tool file under src/tools/** (and its test under tests/unit/**). Use it for every Phase-13 / v0.5.0 feature-build tool and any re-run after a gate failure.

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Build and refine TouchDesigner projects with tdmcp using context-first, visible, reversible workflows.

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Apply fail-closed consent, scope, undo, and verification rules to TouchDesigner mutations made with tdmcp.

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Diagnose tdmcp and TouchDesigner bridge problems with bounded checks and evidence-backed recovery steps.

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Write operator-facing and public documentation plans for AI-Controlled Party mixer/Soundcraft Ui24R scene arming. Use for runbooks, rehearsal checklists, show-day checklists, EN/PT docs updates, demo scripts, safety wording, and follow-up documentation revisions.

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Review, harden, and test the safety policy for AI-Controlled Party mixer/Soundcraft Ui24R scene arming. Use for approval gates, blocked mixer operations, hazardous request handling, venue validation, bypass attempts, QA, risk review, or follow-up safety changes.

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