agentic-review
agentic-review is a Change & PR review skill for AI agents, published by dxos in the dxos repository on GitHub. Skillspace rates agentic-review D (59/100) and it passed the safety scan; the rating is based on static analysis only.
Run the rule-driven agentic code review — discover `rule` blocks in the repo's `.mdl` files, prepare per-rule review groups (full project by default; diff-only with `--pr-only`), spawn one focused Sonnet subagent per group, then finalize the merged diagnostics into REVIEW.md + RESOLUTION.md. Use when asked to run the agentic review, list unresolved review issues, review a branch/PR against the repo's `.mdl` rules, or check a diff for known anti-patterns. For the built-in bug/quality passes use `/code-review` instead.
- Grade
- D
- Quality
- 59 / 100
- Safety
- Passed
- GitHub stars
- 520
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
- 84 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Not checked yet
- Category is a classifier prediction; no model has read this skill 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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