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.
npx agentmods add commands/dreamrec/tdpilot/td-explain-patchgit clone --depth 1 https://github.com/dreamrec/TDPilotWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00021 | $0.00371 |
| Opus 5 | $0.00010 | $0.00186 |
| Sonnet 5 | $0.00004 | $0.00074 |
| Haiku 4.5 | $0.00002 | $0.00037 |
Grade A, and why
td-explain-patch 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 2d 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.
What it actually says
Give the user a clear, honest map of the TouchDesigner project they already have open. This is strictly read-only — do not create, modify, or delete anything.
- Verify the connection with
td_get_info(project name, build, FPS). - Audit. Call
td_audit_projectfor the structural overview, thentd_get_nodeson/project1(and the 2-3 largest child COMPs) to map the real network. Usetd_get_errorsrecursively for problems andtd_cooking_infofor the performance hot spots. - Identify the spine. Find the main signal path(s): sources → processing → output (final TOP / output window). Note dead ends and orphaned nodes.
- Report in this shape, concise and jargon-light:
- What this project is: one-paragraph read of its purpose and style.
- Signal flow: the main chain(s), named node by node.
- Problems found: errors, warnings, broken references — each with the one-line fix.
- Performance: the top cook-time offenders and whether they matter at the project's FPS.
- Three quick wins: concrete, small improvements you could make on request (each one tool call away — but do NOT do them now).
- Offer next steps: "want me to fix any of these?" plus
/td-snapshotbefore any edits.
If the project is empty or nearly empty, say so and point to /td-first-wow
instead of padding an empty audit.
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.
- 2d ago First seen · 30 lines · 21 tokens per session scan A da33bef7755a
td-explain-patch is a command published in the GitHub repository dreamrec/TDPilot (11 stars, last pushed 1mo ago), licensed MIT. It adds 21 tokens to every session and 371 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
develop-image-prompt.eval
Generates a detailed image generation prompt from a document or content description. Good output: a prompt that is specific, visual, non-abstract, includes style/composition/lighting guidance, and is calibrated to the specified dimensions and style options.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.