Performance Review
In /reviewer_review-pr use the PR-session tools above. Standalone (no PR session): use
the session-less tools per the reviewer-grounding block when reviewer is connected and the
index is fresh; otherwise fall back to grep/Read.
Goal
Look only for performance and efficiency risks in the selected changes. Ignore style, architecture, tests, and general correctness unless they materially affect performance.
Prioritize findings such as:
- N+1 queries and repeated remote calls;
- unnecessary loops or repeated work;
- bad asymptotic behavior on hot paths;
- redundant rendering, serialization, parsing, allocations, or avoidable copies;
- missing batching, caching, pagination, or streaming where the diff makes that risk likely;
- blocking I/O or CPU-heavy work on latency-sensitive paths;
- memory growth or large payload handling.
Method
- Read the diff first.
- Open only the nearby code needed to understand whether the changed path is
performance-sensitive. In
/reviewer_review-pruse the reviewer MCP tools:read_file,search_code,find_callers. - Prefer concrete findings over vague perf speculation.
- If a concern depends on an assumption, state that assumption explicitly.
- If a path is probably not performance-sensitive, do not invent issues.
Severity
critical/high: likely severe latency, throughput, or resource regression on an important path.medium: meaningful inefficiency or scaling risk that should probably be fixed.low: worthwhile optimization or preventive note, not a blocker.
Output
Return only actionable findings.
Return ONLY the findings JSON used by the review pipeline, with
"category": "performance":
- Calibrate
confidenceagainst a measurable, reproducible effect: a hot path you can point to (loop bound, query inside a loop) → 0.8+; a plausible but data-dependent cost → 0.5–0.7; no measurable/reproducible effect → ≤ 0.4 (drop). Set "category" to "performance"; "side" is always "RIGHT".
Source: hashgraph-online/awesome-codex-plugins → plugins/mimfort/rag_for_git/plugin/skills/performance-review/SKILL.md