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 skills/cheshirejcat/blender/reference-analysis-validatornpx skills add CheshireJCat/blender --skill reference-analysis-validatorgit clone --depth 1 https://github.com/CheshireJCat/blenderWrote 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/cheshirejcat/blender/reference-analysis-validator)<a href="https://agentmods.dev/skills/cheshirejcat/blender/reference-analysis-validator"><img src="https://agentmods.dev/badge/skills/cheshirejcat/blender/reference-analysis-validator.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00094 | $0.00708 |
| Opus 5 | $0.00047 | $0.00354 |
| Sonnet 5 | $0.00019 | $0.00142 |
| Haiku 4.5 | $0.00009 | $0.00071 |
Grade A, and why
reference-analysis-validator 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 4d 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.
This is a copy
92% identical to reference-analysis-validator — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reference Analysis Validator
This skill converts “looks close” into measurable gates. For brand/logo/mascot work, do not model or export until a source manifest and validation thresholds exist.
Required outputs
Create these in the asset output folder:
reference_manifest.json— classified source files, expected parts, thresholds.source_analysis/*.json— image metadata, masks/components/landmarks.validation/front_overlay_reference.png— reference and render overlay.validation/front_mask_validation.json— IoU/SSIM/bbox/centroid report.
Workflow
- Classify sources: front, side, back, top, texture atlas, decals, maps, lightmap, aura/context.
- Build/refresh
reference_manifest.jsonwith hard expected counts and view roles. - Extract masks/components from each source using
scripts/reference_manifest_compiler.pyor existing analyzers. - Render model from matching orthographic camera with reference planes hidden.
- Compare reference mask vs render mask using
scripts/render_overlay_validator.py. - Refuse final export if hard gates fail.
Modality rule
Compare like with like. A wireframe edge mask compared against a shaded beauty render gives misleadingly low IoU. For hard gates, render a flat silhouette/matte pass from Blender or compare reference edges to render edges. Use render_overlay_validator.py --reference-mode ... --render-mode ... when the source and render need different mask extraction modes.
Default validation gates
- primary structural part count: exact.
- front silhouette IoU: target >= 0.90 for rigid/logotype shapes; >= 0.82 acceptable for first mascot reconstruction pass.
- bbox center drift: <= 12 px at 1024 px validation size.
- bbox size drift: <= 3% of image dimension.
- face/eye/smile landmark drift: <= 2% of image dimension when landmarks are defined.
Failure policy
If a repeated mismatch occurs, record the measured failure, then route to the missing specialty skill:
- wrong silhouette →
contour-to-mesh - wrong depth/side/back →
orthographic-registration - wrong textures →
atlas-uv-fitting - wrong whole workflow →
mascot-logo-reconstruction
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 63 lines · 94 tokens per session scan A 03e09576db1d
reference-analysis-validator is a skill published in the GitHub repository CheshireJCat/blender (23 stars, last pushed 15d ago), licensed MIT. It adds 94 tokens to every session and 708 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to reference-analysis-validator, differing in 4 lines, and is treated as a copy.
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