td-feature-design

td-feature-design is a skill for Claude Code, Codex from Pantani/tdmcp. It costs 110 tokens per session (952 once invoked), scanned A, original, MIT.

A planning workflow for designing features for tdmcp, a system that lets an agent control TouchDesigner. It produces an implementation-ready specification covering the feature's location, inputs, network structure, bridge code, interface, risks, and tests.

In plain words
What is it for?
Use it to turn a TouchDesigner feature idea into a concrete build plan, choose the appropriate feature layer, define input validation, map the node network, and plan testing.
Why use it?
It prevents important design decisions from being made inconsistently during coding. The specification gives the builder a clear file location, input structure, and verification plan before implementation begins.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents); mentions AGENTS.md.

Good fit Use it to turn a TouchDesigner feature idea into a concrete build plan, choose the appropriate feature layer, define input validation, map the node network, and plan testing.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pantani/tdmcp/td-feature-design
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Pantani/tdmcp --skill td-feature-design
Clone the repo
git clone --depth 1 https://github.com/Pantani/tdmcp

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for td-feature-design

README.md
[![agentmods](https://agentmods.dev/badge/skills/pantani/tdmcp/td-feature-design/github.svg)](https://agentmods.dev/skills/pantani/tdmcp/td-feature-design)
Your own site
<a href="https://agentmods.dev/skills/pantani/tdmcp/td-feature-design"><img src="https://agentmods.dev/badge/skills/pantani/tdmcp/td-feature-design/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for td-feature-design

Your own site · 80×15
<a href="https://agentmods.dev/skills/pantani/tdmcp/td-feature-design"><img src="https://agentmods.dev/badge/skills/pantani/tdmcp/td-feature-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 110 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 952 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00110 $0.00952
Opus 5 $0.00055 $0.00476
Sonnet 5 $0.00022 $0.00190
Haiku 4.5 $0.00011 $0.00095

Measured 10d ago against content hash d69122197019, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

td-feature-design scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

.agents/skills/td-feature-design/SKILL.md · 37 lines

How it starts

The opening of the file, as written. The whole thing — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.

td-feature-design — turn an idea into an implementable spec

A spec is good when a builder can implement it in one file + one test without re-deciding anything. Aim for that bar.

Procedure

  1. Read the context first. 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.
  2. Pick the layer / altitude:
    • Layer 1 (src/tools/layer1/) — an artist tool that builds a whole wired+arranged network (goes through orchestration.ts).
    • Layer 2 (src/tools/layer2/) — a building block (connect, control panel, animate, external IO).
    • Layer 3 (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).
    • Decide the file path now: src/tools/layer<N>/<camelCaseName>.ts.
  3. Design the Zod input schema — a param table: name, type, default, enum values, notes. Defaults matter: device-sourced inputs (camera/audio) default to a synthetic/file source (live device is opt-in) because device capture can hang TD on a macOS permission modal.
  4. Lay out the TD network topology — the operators it creates, how they wire, and the live controls it exposes. Reactive features must end on a Null CHOP ready for 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.
  5. Plan the bridge approach — almost always a Python payload via buildPayloadScript (__PAYLOAD_B64__) executed through the client and parsed with parsePythonReport. Propose a new REST endpoint only when streaming or performance genuinely demands it.
  6. Sketch a UI wireframe when the feature has a surface (control panel / control surface / phone remote / web dashboard / chat UI): an ASCII layout or component list naming each control and what parameter it drives.
  7. List probe-first risks — anything to validate live before locking the API: platform-specific operators (Syphon/Spout/NDI/Video-Stream-Out exist only on some OS/licenses), KB-missing operators (the KB lags ~14 recent ops; ~22 dir(td) names aren't createable), device permissions, and time-dependent chains that read 0 on a paused timeline.
  8. Write the test plan — what the offline msw unit test should assert (operators created, params set, wiring, the returned shape).
  9. Write integration notes — exactly which shared files the integrator must edit (layer*/index.ts, src/cli/agent.ts command name + flags, docs regenerate automatically).

Read the full file on GitHub · 37 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 37 lines · 110 tokens per session scan A d69122197019

Subscribe to this mod's changes

td-feature-design is a skill published in the GitHub repository Pantani/tdmcp (39 stars, last pushed 25d ago), licensed MIT. It adds 110 tokens to every session and 952 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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