automated-code-review
Skill3 starsChanged 3 months agoMITView on GitHub
Systematic review execution engine -- transforms structured human review coaching patterns into autonomous review checklists with pass/fail gates, convention detection, and structured finding production. Use when running autonomous code reviews to ensure systematic coverage and consistent quality.
In this repository86 other files it gives its agents.
- AGENTS.mdAGENTS.md
- project-templates/AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- project-templates/CLAUDE.mdCLAUDE.md
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The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 57
Exit criteria: all five categories evaluated for every in-scope file against detected conventions.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Automated Code Review
"Inspection at the source is called prevention. Inspection after the fact is called sorting." -- W. Edwards Deming
Core Philosophy
Code review coaching teaches humans how to review; automated code review teaches agents how to execute reviews systematically — the difference between a textbook and a manufacturing process. This skill converts the CACR (Challenge-Attempt-Compare-Reflect) coaching framework into an execution framework: systematic checklists with explicit pass/fail gates that prevent superficial reviews, and convention detection that calibrates findings to the project's own standards rather than abstract ideals. A coaching skill teaches a human to ask "did I check error handling?"; this skill tells the agent exactly HOW — enumerate every fallible call, verify each has an error path, verify the path handles rather than swallows, verify the message carries diagnostic context.
It does NOT teach review principles — it assumes those from code-review-coach and
security-review-trainer. It provides the operational framework: checklists, gates, convention
detection, and structured output that turn review knowledge into consistent execution.
Non-Negotiable Constraints:
- SYSTEMATIC COVERAGE — every category is checked against a concrete checklist; the checklist is the floor, never skipped.
- CONVENTION CALIBRATION — detect the project's conventions before reporting any style finding; external-standard findings on a differing project are false positives.
- PASS/FAIL GATING — each phase has explicit exit gates; a phase cannot advance until its gate passes.
- EVIDENCE PER FINDING — every finding carries line numbers + snippet; severity reflects impact in the project's actual context.
- FALSE-POSITIVE PREVENTION — verify against framework, middleware, and surrounding code before reporting; ambiguous findings are flagged "needs verification."
Full principle table, knowledge-base grounding, detailed phase gates, the finding pipeline, and the
minimum checklists live in references/conventions.md.
Workflow
SCAN Define scope; enumerate files with languages; detect project conventions (procedures in
references/convention-detection.md). GATE: scope defined, conventions detected, ≥3 files sampled.
ANALYZE Read each file completely. Run all five category checklists per file (floor in
conventions.md; detail in review-checklist-engine.md). The maintainability category
uses the Fowler code smell catalog (references/code-smells.md) as its canonical
checklist, with the "repo overrides" suppression rule. Record findings via the finding
pipeline. GATE: every file analyzed, every category checked, every finding has evidence +
severity + false-positive check.
SYNTHESIZE De-duplicate, cross-reference, rank by severity, group into themes. GATE: consolidated
list false-positive reviewed.
REPORT Produce structured output (templates in references/output-templates.md). GATE: every
finding has evidence/category/severity/fix; ordered critical-first; positives + stats included.Exit criteria: all five categories evaluated for every in-scope file against detected conventions; every finding evidenced and severity-justified; false positives filtered; structured report produced with positive observations and statistics.
State Block
<automated-review-state>
phase: SCAN | ANALYZE | SYNTHESIZE | REPORT | COMPLETE
scope: [diff | files | directory | PR]
conventions_detected: true | false
files_total: [N]
files_analyzed: [N]
findings: [count by severity — C/H/M/L/Nit]
false_positives_filtered: [N]
last_action: [description]
next_action: [description]
</automated-review-state>Output Template
- Per-file analysis log, consolidated report, review statistics —
references/output-templates.md. - Detailed per-category checklists, pass/fail criteria, language extensions —
references/review-checklist-engine.md. - Fowler code smell catalog (the maintainability-category checklist) + repo-overrides rule —
references/code-smells.md. - Convention detection procedures (naming, error handling, logging, testing) —
references/convention-detection.md. - Principle table, KB lookups, full phase gates, finding pipeline, minimum checklists —
references/conventions.md.
Integration with Other Skills
| Skill | Relationship |
code-review-coach | Provides the review rubric, scoring methodology, and category definitions this skill operationalizes. Coach teaches what to look for; this skill ensures nothing is skipped. |
security-review-trainer | Provides deep security patterns and OWASP mapping. The security checklist here is a minimum; the trainer expands it with level-appropriate subtlety. |
pr-feedback-writer | Shapes how findings are communicated. After this skill produces findings, pr-feedback-writer frames them as constructive, actionable PR comments. |
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