panel-review
panel-review is a Multi-agent review & consensus skill for AI agents, published by chrisreddington in the flight-school repository on GitHub. Skillspace rates panel-review D (55/100) and it passed the safety scan; the rating is based on static analysis only.
Use whenever you are planning, executing, or finishing any non-trivial architectural change — multi-file refactors, cross-cutting cleanups, performance work, new subsystems, or anything where "wrong design" costs more than "wrong implementation". Convenes a six-reviewer panel (three models × two personas) that critiques the plan before code lands and re-reviews every milestone until consensus. Trigger phrases: "architecture cleanup", "design review", "panel review", "rubber-duck this plan", "non-trivial refactor", "before I implement", "is this approach sound", "get this critiqued".
- Grade
- D
- Quality
- 55 / 100
- Safety
- Passed
- GitHub stars
- 30
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
- 77 / 100
- Maturity
- Basic: a single SKILL.md
- 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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