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 RobLe3/cc-blender-skill --skill landmark-fit-repairgit clone --depth 1 https://github.com/RobLe3/cc-blender-skillWrote 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/roble3/cc-blender-skill/landmark-fit-repair)<a href="https://agentmods.dev/skills/roble3/cc-blender-skill/landmark-fit-repair"><img src="https://agentmods.dev/badge/skills/roble3/cc-blender-skill/landmark-fit-repair/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/roble3/cc-blender-skill/landmark-fit-repair"><img src="https://agentmods.dev/badge/skills/roble3/cc-blender-skill/landmark-fit-repair.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk 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 | $0.00063 | $0.00654 |
| Opus 5.5 | $0.00025 | $0.00262 |
| Sonnet 5.5 | $0.00013 | $0.00131 |
| Haiku 4.5 | $0.00006 | $0.00065 |
Grade A, and why
landmark-fit-repair 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 13d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- landmark-fit-repair — 86% identical, 9 lines differ
How it starts
The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCP backend
Use when: Landmark validation, feature-point deltas, control-point repair, face/eye/smile alignment, leaf tip alignment, aura ring fitting, iterative recipe parameter updates.
Before the first Blender call, read ../text-to-blender/references/mcp-backends.md. Prefer official MCP for shared capabilities; preserve the selected backend for the whole task. Tool names in recipes are client/legacy examples: map them through that reference and its agent-host guide.
Landmark Fit Repair
Bbox and IoU are too coarse for final mascot/logo matching. This skill turns named feature drift into recipe edits.
Landmark classes
structural_tip: outer part tips and extrema;shell_corner: face/shell/rim corners;feature: eyes, smile, brows, decals;ring: aura center/radius/dots;depth_marker: side/back/top thickness markers.
Workflow
- Define a landmark JSON for the source reference.
- Detect or render corresponding product landmarks.
- Compare by name and view.
- Convert deltas into repair actions: move boundary control point, scale one component, shift feature curve, tune depth, or adjust aura radius.
- Rebuild from recipe; do not hand-edit final geometry without updating the recipe/manifest.
Hard gates
- No final export when named structural landmarks exceed tolerance.
- Face features must be validated separately from body silhouette.
- Aura/context landmarks must not affect base GLB acceptance.
Script
scripts/landmark_fit_report.pycompares two named-landmark JSON files and emits repair deltas.
Landmark JSON schema
{
"schema": "landmarks.v1",
"image_size": [width, height],
"landmarks": [
{"view":"front", "name":"leaf_top_tip", "class":"structural_tip", "x":627, "y":130}
]
}
For part masks, generate initial landmarks from extrema: top/bottom/left/right, centroid, and contour inflection points. Then rename them to semantic names before repair.
What ships with it
1 file 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.
- 13d ago Changed · +5 lines f18155b8622f
- 1mo ago First seen · 52 lines · 63 tokens per session scan A 1785461cd985
landmark-fit-repair is a skill published in the GitHub repository RobLe3/cc-blender-skill (125 stars, last pushed 14d ago), licensed MIT. It adds 63 tokens to every session and 654 once invoked, about $0.0003 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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