review-runtime-reliability-performance

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Use when reviewing pull requests for failure semantics, concurrency lifecycle safety, and performance scalability risks before merge.

D3Hunter By D3Hunter schedule Updated 3/3/2026

name: review-runtime-reliability-performance description: Use when reviewing pull requests for failure semantics, concurrency lifecycle safety, and performance scalability risks before merge.

Review Failure Semantics, Concurrency Lifecycle, and Performance

Overview

Use this skill to identify reliability and scalability issues in behavior-changing pull requests. Focus on failure contracts, retry/timeout/cancellation behavior, concurrency ownership and lifecycle discipline, and performance risks under realistic load.

This skill covers discovery only. After findings are identified, hand off output rendering to review-output-format.

This is a static-analysis-first review flow. Do not run build/test commands directly as part of this skill.

Input

This skill accepts exactly three input parameters:

  • code_path (required): absolute path to the cloned codebase; this is the working directory for review.
  • diff_filename (required): filename of the diff to review.
  • output_filename (required): final output JSON filename for the rendered findings payload.

Output

  • Final output must be a file named exactly as output_filename.
  • File content format is already defined by review-output-format.
  • Do not invent or emit an alternate output schema.

Review Flow

  1. Scope the review surface

    • Use code_path as the working directory.
    • Load and review changes from diff_filename as the primary review scope.
    • Identify changed boundaries that can fail or saturate: API handlers, async workers/jobs, scheduler loops, retry loops, queueing paths, lock/transaction paths, and external dependency calls.
  2. Run full checklist pass

  3. Evaluate potential issues with objective evidence

    • Confirm at least one objective signal:
      • failure contract ambiguity or silent failure path
      • retry/idempotency/timeout mismatch with dependency behavior
      • cancellation, lifecycle, or synchronization race/leak risk
      • unbounded parallelism, queue growth, or overload collapse risk
      • measurable performance/scaling anti-pattern in hot paths
    • If evidence is weak, request targeted validation instead of asserting a defect.
  4. Assign severity for handoff

    • Blocker: high-confidence data integrity/safety break, deadlock risk, destructive failure-mode bug, or collapse risk under expected load.
    • Major: high-confidence reliability/concurrency/performance risk with meaningful user or operational impact.
    • Minor: localized risk with limited blast radius.
    • Info / Nit: low-risk observation, clarification, or polish.
  5. Prepare findings payload

    • One issue per finding.
    • For each finding include:
      • severity
      • title
      • why
      • scope
      • risk_if_unchanged
      • evidence
      • change_request
    • Keep scope concrete (path:line, module, branch, or scenario boundary).
  6. Required output handoff

    • After the checklist pass is complete, invoke review-output-format.
    • Render final findings strictly with that skill's output contract.
    • Write that JSON to output_filename.

Runtime Validation Policy

  • Never execute project build commands during this review flow.
  • Never execute project test commands during this review flow.
  • Never run broad verification tasks directly in this skill.
  • If runtime confirmation is needed, request targeted validation with a minimal scenario and exact command, but do not run it yourself.
  • Keep review latency low by relying on diff evidence, failure-model reasoning, and local code-path context.

Review Depth Rules

  • Do not emit a no-findings conclusion until every checklist section is passed or explicitly N/A.
  • Prioritize failure-mode and lifecycle correctness over style feedback.
  • For non-trivial findings, include at least one concrete scenario (trigger/condition -> incorrect outcome).
  • Treat retry/idempotency mismatches and cancellation leaks as high-risk by default.
  • Treat p99/tail-latency regressions and overload-path weaknesses as first-class risks.
  • If uncertain, ask for focused validation rather than making a hard claim.

References

Install via CLI
npx skills add https://github.com/D3Hunter/ai-engineer --skill review-runtime-reliability-performance
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