| schemaVersion | 2026-04-11T00:00:00.000Z |
| skillId | review/code-review-risk-based |
| name | code-review-risk-based |
| displayName | Risk Based Code Review |
| description | Use when working on high-risk diffs touching auth, payments, data loss, concurrency, migrations, or public APIs. Focus on blast radius, invariants, rollback, observability, and edge cases. |
| aliases | ["code-review-risk-based","Risk Based Code Review","code review risk based","codereviewriskbased","代码实现","代码审查","code review","评审","风险审查","risk-based","risk","based","服务端","server side"] |
| version | 0.1.0 |
| sourceHash | sha256:2d538d7164e8fc979266af0cbbf7fd12db9d929e302f55e439496980856b6af3 |
| domain | review |
| departmentTags | ["backend-platform"] |
| sceneTags | ["review","architecture"] |
Risk Based Code Review
Use this skill when the task involves high-risk diffs touching auth, payments, data loss, concurrency, migrations, or public APIs.
Goal: produce reliable engineering guidance and implementation steps focused on blast radius, invariants, rollback, observability, and edge cases.
Working model
- Identify the affected system, data, users, and failure modes.
- Define invariants, inputs, outputs, ownership, and rollback needs.
- Prefer small, auditable changes with explicit validation.
- Call out security, performance, concurrency, and data-loss risks when relevant.
- Finish with concrete verification steps and residual risks.
Rules
- Ground recommendations in the current codebase or runtime evidence.
- Prefer explicit contracts, typed boundaries, and defensive validation.
- Do not hide operational concerns behind generic best practices.
- Include negative cases, edge cases, and failure behavior.
- For review tasks, list findings first with file and line references when possible.
- For test or performance tasks, define the workload, success criteria, and measurement method.
Checklist
- Are assumptions and ownership boundaries explicit?
- Are risky changes reversible or safely deployable?
- Are observability and diagnostics sufficient for production issues?
- Are tests or validation steps targeted to the actual risk?
- Are security and data-integrity concerns addressed?
