landmark-fit-repair
Validate and repair source-locked Blender models using named landmarks such as leaf tips.
What this skill does for you
Validate and repair source-locked Blender models using named landmarks such as leaf tips, shell corners, eyes, smile, rim thickness, aura center/radius, and view-specific depth markers. Use when bbox/IoU is insufficient and the model must align to templates at designed feature points.
Quoted from the skill description in the pinned sourceWho made it
Use it with Edge
Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the landmark-fit-repair skill from roble3/cc-blender-skill.
Paste it into Claude, ChatGPT, Codex or Cursor.
Or read the skill source first.
Security evidence
| Scanner | Date | Result | Findings |
|---|---|---|---|
| Edge static checks | 2026-09-27 | Pass | 0 |
| Cisco skill-scanner | 2026-09-27 | Pass | 0 |
| Semgrep Edge rules | 2026-09-27 | Pass | 0 |
Static scans check the code, not how well the skill works.
Scanner scope, raw findings and mirrored provider records
Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: 11016c9a5847897491dde935c346571bd7548e3d. Raw findings: . Counted findings: .
Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: 11016c9a5847897491dde935c346571bd7548e3d. Raw findings: 1. Counted findings: .
Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: 11016c9a5847897491dde935c346571bd7548e3d. Raw findings: . Counted findings: .
Source and licence
- Repository
- https://github.com/roble3/cc-blender-skill
- Pinned skill file
- View source at revision
- Revision
- 11016c9a5847897491dde935c346571bd7548e3d
- Package hash
- sha256:fe61160696eb72f7623d3d99e29798a1142d185a069a17aae2950c98d0cff297
- Licence
- MIT