| schemaVersion | "2026-04-11T00:00:00.000Z" |
| skillId | review/code-review-general |
| name | code-review-general |
| displayName | General Code Review |
| description | Use when working on general code review across frontend, backend, scripts, and infrastructure changes. Focus on bugs, regressions, maintainability risks, and missing tests. |
| aliases | ["code-review-general","General Code Review","code review general","codereviewgeneral","代码实现","代码审查","code review","评审","服务端","server side"] |
| version | 0.1.0 |
| sourceHash | sha256:29276f5d3edf1f1aef29beab0b0147ec135fae251dd46f24179b573b83d0350e |
| domain | review |
| departmentTags | ["backend-platform"] |
| sceneTags | ["review"] |
General Code Review
Use this skill when the task involves general code review across frontend, backend, scripts, and infrastructure changes.
Goal: produce reliable engineering guidance and implementation steps focused on bugs, regressions, maintainability risks, and missing tests.
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?
