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 skills add dylanroscover/Embody --skill specimen-authoringgit clone --depth 1 https://github.com/dylanroscover/EmbodyWrote 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.
[](https://agentmods.dev/skills/dylanroscover/embody/specimen-authoring)<a href="https://agentmods.dev/skills/dylanroscover/embody/specimen-authoring"><img src="https://agentmods.dev/badge/skills/dylanroscover/embody/specimen-authoring/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.
<a href="https://agentmods.dev/skills/dylanroscover/embody/specimen-authoring"><img src="https://agentmods.dev/badge/skills/dylanroscover/embody/specimen-authoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00038 | $0.06050 |
| Opus 5.5 | $0.00015 | $0.02420 |
| Sonnet 5.5 | $0.00008 | $0.01210 |
| Haiku 4.5 | $0.00004 | $0.00605 |
Grade A, and why
specimen-authoring 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Specimen Authoring
How to build a Specimen for the Embody Collection -- a transparent, reusable TDXN network that demonstrates a TouchDesigner technique. Two specimens set the bar: reaction-diffusion (generative, a GPU feedback simulation) and kaleidoscope (compositing, a reusable polar-mirror component).
The bar -- every Specimen must clear it
- Clear use -- a user can finish "I'd use this for ___" (a VJ loop, a drop-in component, a texture/displacement source, a real learning reference).
- Non-obvious technique -- a "how'd they do that?" moment, not a one-TOP drag.
- Striking -- worth opening and exploring.
- Drop-in -- clean input/output, exposed parameters, self-contained, bounded for performance.
Generic noise plus a colorize is NOT a specimen. If a beginner makes it by accident, cut it.
Workflow (one at a time)
- Build in the sandbox COMP
/specimen_lab/<name>(NOT inside the Embody COMP -- the toe file, somewhere neutral). Iterate freely there. - Gate performance (see
performance.md): baselineget_project_performancebefore, re-check after each heavy step. Feedback loops and GLSL are the usual cost. fps below ~90% of target is a stop condition -- optimize before continuing. Beware: a concurrentcapture_topornumpyArray()stalls the GPU and makes the fps reading dip; take a clean reading without them. - Verify it actually animates and cooks before believing it -- see "Cook demand" below. Never claim animation from a single forced capture.
- Judge the look by actually looking --
capture_topthen read the frame; loadvisual-aesthetics.capture_topforce-cooks, so it can show a frame your live (undemanded) viewer is NOT showing -- a stale viewer and a fresh capture are different frames; that mismatch is real, not a hallucination. - Ask the user to review before persisting. Persist only when it is genuinely good, animating, and clean.
Cook demand -- the trap that bit both specimens
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.
- 6d ago Changed · +4 lines 9ae15dac2610
- 1mo ago Changed · +22 lines f7451f332055
- 1mo ago Changed · +6 lines d250c60fc350
- 1mo ago First seen · 131 lines · 38 tokens per session scan A 4bc790438f27
specimen-authoring is a skill published in the GitHub repository dylanroscover/Embody (208 stars, last pushed 2d ago), licensed MIT. It adds 38 tokens to every session and 6,050 once invoked, about $0.0002 per session on Opus 5.5. 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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