assess
assess is a Codebase audits & code health skill for AI agents, published by bjcoombs in the ai-native-toolkit repository on GitHub. Skillspace rates assess C (76/100) and it passed the safety scan; the rating is based on static analysis only.
Assess a codebase's readiness for AI agent contributors using the layered contract model, and generate a complexity hotspot SVG treemap (size = LOC, hue = cyclomatic complexity, saturation = recent git churn). TRIGGER when the user types /assess, asks for an AI-readiness review, wants a complexity heatmap or hotspot map, asks 'how complex is this code?', wants migration risk triage, or asks for a codebase snapshot/report. Produces an MD report + SVG that can be opened as a PR in the target repo.
- Grade
- C
- Quality
- 76 / 100
- Safety
- Passed
- GitHub stars
- 29
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 91 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Apache-2.0
- 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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