AgentSkillsCN

code-review

自动化代码审查工作流。阅读任务简报,检查边界,核对验收标准,排查回归问题,并给出“通过”或“不通过”的评审结论。

SKILL.md
--- frontmatter
name: code-review
description: Automated code review workflow. Reads task brief, checks boundaries, verifies acceptance criteria, checks for regressions, and produces an APPROVE or REJECT verdict.
type: flow
mermaid
flowchart TD
    A([BEGIN]) --> B[Read task brief and acceptance criteria from .ai/tasks/]
    B --> C[Read git diff of submitted changes]
    C --> D[Check: are all modified files within agent boundary?]
    D --> E{Boundary violation?}
    E -->|Yes| F["REJECT: list boundary violations in .ai/reviews/"]
    F --> Z([END])
    E -->|No| G[Check each acceptance criterion against the diff]
    G --> H{All criteria met?}
    H -->|No| I["REJECT: list unmet criteria in .ai/reviews/"]
    I --> Z
    H -->|Yes| J[Check for regressions: build, tests, related features]
    J --> K{Regressions found?}
    K -->|Yes| L["REJECT: describe regressions in .ai/reviews/"]
    L --> Z
    K -->|No| M[Check commit message format compliance]
    M --> N{Format correct?}
    N -->|No| O["CHANGES REQUESTED: fix commit message format"]
    O --> Z
    N -->|Yes| P["APPROVE: generate review report in .ai/reviews/"]
    P --> Q[Commit approve with routing header]
    Q --> Z

Flow Steps Detail

Step: Read task brief

  • Open .ai/tasks/TASK-XXX.md
  • Extract acceptance criteria checklist
  • Note the assigned agent and file scope

Step: Read git diff

  • Run git diff pre-mortal..<agent>/<task-id>
  • Identify all modified, added, and deleted files
  • Note the scope of changes

Step: Check boundaries

  • Compare modified files against AGENTS.md ownership
  • Reference .ai/boundaries.md for the complete map
  • Flag any file outside the agent's domain

Step: Check acceptance criteria

  • Go through each criterion one by one
  • Mark as met or unmet
  • For unmet criteria, note what's missing

Step: Check for regressions

  • Verify build passes: npm run build
  • Verify tests pass: npm run test
  • Verify type check passes: npx tsc --noEmit
  • Check related features still work

Step: Check commit message format

  • Verify header: [AGENT:x] [ACTION:submit] [TASK:z]
  • Verify AGENT value matches the submitting agent
  • Verify TASK value matches the task being reviewed

Step: Generate review report

  • Write to .ai/reviews/TASK-XXX-review.md
  • Include checklist, findings, feedback, and verdict
  • Use template from .ai/templates/review.md

Verdict Outcomes

VerdictCommitNext Action
APPROVE[AGENT:kimi] [ACTION:approve] [TASK:X]Merge to pre-mortal
CHANGES REQUESTED[AGENT:kimi] [ACTION:reject] [TASK:X]Agent fixes and re-submits
REJECT[AGENT:kimi] [ACTION:reject] [TASK:X]Task re-scoped or reassigned

Advanced Review Patterns

Dynamic Reviewer Subagents

For specialized reviews, create a dynamic subagent at runtime:

python
CreateSubagent(name="security-reviewer", system_prompt="<security review prompt>")
Task(subagent_name="security-reviewer", prompt="Review TASK-X for security issues...")

Templates available in .agents/subagents/ (debugger, performance, docs, test-generator).

Agent Swarm for Batch Reviews

At sprint end, dispatch multiple reviewer subagents in parallel:

python
# Review 5 tasks simultaneously (K2.5 supports up to 100 sub-agents)
for task in tasks:
    Task(subagent_name="reviewer", prompt=f"Review {task}...")

See .ai/patterns/agent-swarm-parallel-review.md for the full pattern.