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 CheshireJCat/blender --skill mascot-logo-reconstructiongit 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/mascot-logo-reconstruction)<a href="https://agentmods.dev/skills/cheshirejcat/blender/mascot-logo-reconstruction"><img src="https://agentmods.dev/badge/skills/cheshirejcat/blender/mascot-logo-reconstruction/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/cheshirejcat/blender/mascot-logo-reconstruction"><img src="https://agentmods.dev/badge/skills/cheshirejcat/blender/mascot-logo-reconstruction.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00066 | $0.00746 |
| Opus 5.5 | $0.00026 | $0.00298 |
| Sonnet 5.5 | $0.00013 | $0.00149 |
| Haiku 4.5 | $0.00007 | $0.00075 |
Grade A, and why
mascot-logo-reconstruction 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 2mo 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
86% identical to mascot-logo-reconstruction — 9 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mascot / Logo Reconstruction
This is the top-level skill for 1:1 brand mascot reconstruction. It chains the specialized skills and enforces stop/go gates.
Harmonization requirement
For mascot/logo work, use blender-skill-harmonizer first when multiple source types or validation failures are present. It sets canonical source policy and prevents conflicts between reconstruction, UV, fit-repair, lighting, export, and animation skills.
Skill chain
reference-analysis-validator— source inventory, manifest, part counts, masks.orthographic-registration— shared front/side/back/top coordinate contract.contour-to-mesh— structural meshes from measured silhouettes.atlas-uv-fitting— per-part texture/UV fitting.blender-materials/blender-lighting— only after geometry and UVs pass.reference-analysis-validatoragain — overlay gates before export.blender-export— export only after gates pass.blender-animation— only after static model is accepted.
Non-negotiable order
Static reference fidelity comes before animation and beauty rendering.
measure → manifest → contour meshes → depth registration → UV fit → overlay validation → export → animation
Hard gates
- expected structural part count equals Blender scene/export structural part count.
- front silhouette overlay passes threshold.
- face/features landmarks pass tolerance.
- side/back/top renders match their registered envelopes.
- texture atlas regions are mapped per part.
- optional aura/background is separated from base structural GLB.
Modeling guidance
- Treat mascots/logos as designed symbols, not natural objects. Symmetry is not guaranteed.
- Do not infer hidden leaves/petals from radial math.
- Avoid primitive-first construction when a silhouette exists.
- Use semantic object names and validation prints.
Source-manifest structural part invariant
Create exactly the structural parts declared by the source manifest. Extra background arcs, glow, aura, shadows, guide marks, and decorative rings are context/decor unless the manifest explicitly promotes them to structural geometry.
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.
- 2mo ago First seen · 73 lines · 66 tokens per session scan A b50be8701411
mascot-logo-reconstruction is a skill published in the GitHub repository CheshireJCat/blender (71 stars, last pushed 13d ago), licensed MIT. It adds 66 tokens to every session and 746 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to mascot-logo-reconstruction, differing in 9 lines, and is treated as a copy.
mascot-logo-reconstruction compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| mascot-logo-reconstructionCheshireJCat/blender | Skill | 71 | 13d ago | MIT | A | 66 | Claude Code |
| steve-jobs-perspectivealchaincyf/nuwa-skill | Skill | 38k | 3d ago | MIT | A | 178 | Claude Code, Codex |
| figma-generate-designDevin-AXIS/iPolloWork | Skill | 7.4k | yesterday | none | A | 192 | Claude Code |
| wireframe-to-3dRobLe3/cc-blender-skill | Skill | 144 | 25d ago | MIT | A | 199 | Claude Code |
| figma-useDevin-AXIS/iPolloWork | Skill | 7.4k | yesterday | none | A | 114 | Claude Code |
| figma-code-connectDevin-AXIS/iPolloWork | Skill | 7.4k | yesterday | none | A | 57 | Claude Code |
| figma-generate-libraryDevin-AXIS/iPolloWork | Skill | 7.4k | yesterday | none | A | 146 | Claude Code |