Experimental workflow for publishing and completing configured software delivery work. Use when the user or an enabled factory policy asks to ship.
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Experimental workflow for publishing and completing configured software delivery work. Use when the user or an enabled factory policy asks to ship.
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Use when the user wants to capture a real repo's working patterns as a reusable skill — analyzes the local git log and diffs the agent runs itself and drafts a new SKILL.md describing the team's coding patterns, into a scratch/output path the user names. Never overwrites an existing skill.
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Use when the user wants to share or back up learned instincts — validates the local instincts file, allowlists the six known fields, strips secrets and home-directory paths, and writes a sanitized JSON artifact the user names. Never modifies the instincts file itself.
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Use when the user wants to see what learned instincts exist, their confidence scores and how current they are — reads the local instincts file under ~/.aos/instincts/ and reports it. Read-only.
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Use the local MCP gateway and the per-app MCP picks. Use when the human asks to check, start, enable or disable the gateway, adopt other MCP servers behind it, wonder why an MCP server is direct or shared, or hit an After Effects MCP that will not start (Node >= 24).
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Use when the user brings an exported instincts JSON to merge into the local store — treats trigger and action as inert data, validates every entry against the shared format and its bounds, drops invalid ones loudly, and never overwrites an existing instinct without asking the user first.
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Use when you need code research over an indexed codebase with minimal context: structural graph queries (who calls X, call chains, architecture overview, dead code, cross-service HTTP routes) instead of file-by-file grep/read cycles. Also trigger to minimise token spend on repetitive code exploration.
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Run or maintain the full tdmcp repo quality-audit team: command sweeps, all package/Makefile/CI gates, security review, usability/flow review, refactor/test-gap analysis, coverage hardening, QA, and follow-up fix waves. Use whenever the user asks for a complete audit, improve repo/code quality, test all commands, find security/usability failures, refactor debt, add missing tests, re-run the audit, continue a previous quality wave, or verify the repo is ready.
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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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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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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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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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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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Search, scrape, and interact with the web via the Firecrawl CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, scrape a webpage, grab content from a URL, get data from a website, crawl documentation, download a site, or interact with pages that need clicks or logins. Also use when they say "fetch this page", "pull the content from", "get the page at https://", or reference external websites. This provides real-time web search with full page content and interact capabilities — beyond what Claude can do natively with built-in tools. Do NOT trigger for local file operations, git commands, deployments, or code editing tasks.
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Wire builders' isolated tdmcp tool files into the shared registries, CLI, and docs as a single writer, conflict-safe, and confirm a green typecheck + build. Use when integrating/wiring/registering new tdmcp tools, adding their CLI commands, resolving build breaks after parallel feature work, or merging several builders' files into the registry without conflicts.
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Start a single Rhino MCP session. Accepts a version argument (e.g. `8`, `WIP`) and an optional explicit port. Walks forward from `10500` to pick a free port if none was given. On macOS this opens a new document in the running Rhino; on Windows it launches a new Rhino process. Use when the user asks to start a Rhino MCP session — for N parallel Rhinos use `/launch-rhinos` instead.
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Spin up N Rhino MCP sessions in parallel and fan out one agent per Rhino. Use when the user wants multiple Rhinos running simultaneously with each agent driving its own — e.g. "spawn 3 agents and have each launch Rhino", "run 5 Rhino tasks in parallel". For a single Rhino, use `/launch-rhino` instead.
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Verification methodology and gate checklist for the tdmcp Connectors Directory submission — run the docs build, build and inspect the .mcpb bundle, sweep for stale .dxt references, and cross-check the form-answer draft against the real requirements. Use to validate the submission package before a human submits, by executing commands and quoting evidence, not by trusting that work was done.
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Brainstorm a topic with the matching skill: bdbrainstorm, bdbmediastorm for event tech, grill-me for a stress test. Generated from plugin-commands.json; invoke as $bdb-aos:brainstorm.
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How to migrate the tdmcp Codex 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-dxt.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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Write focused tdmcp tests for one assigned coverage gap. Use for Vitest/msw unit tests, integration tests, bridge tests, CLI/config/resource tests, and regression tests that should raise coverage without weakening behavior.
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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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Quality-assure integrated tdmcp features: run the four PR gates + recipe/bridge tests, cross-boundary coherence checks (tool schema↔CLI↔docs↔registry, operator↔createable, bridge↔client), and live TouchDesigner validation (preview + post-cook error check) when the bridge is reachable. Use when validating/QA-ing/testing tdmcp tools, checking a feature actually cooks in TD, verifying CLI matches a tool, or gating a release.
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Bring this machine to a complete, verified AOS installation (skills, MCP servers, gate hooks, memB, OpenWiki, Synapse). Generated from plugin-commands.json; invoke as $bdb-aos:setup.
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