nanodevice_flakedetect
nanodevice_flakedetect is a Computer vision skill for AI agents, published by caidish in the KlayoutClaw repository on GitHub. Skillspace rates nanodevice_flakedetect C (73/100) and it passed the safety scan; the rating is based on static analysis only.
Detect and map van der Waals heterostructure flake boundaries from microscope images into KLayout polygons. Split workflow with 5 sub-skills (align, detect, combine, commit, review) for agent-orchestrated stack detection. Use this skill when the user wants to detect flakes from multiple source images, align cross-substrate images, segment hBN/graphene/graphite stacks, or run the full stack detection pipeline.
- Grade
- C
- Quality
- 73 / 100
- Safety
- Passed
- GitHub stars
- 27
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 97 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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