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review-tests
Comprehensive test review using parallel test-reviewer agents.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Comprehensive test review using parallel test-reviewer agents.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Create, list, and resolve review issues. Critical issues get individual files for research; warnings and gaps go to a quick-fix checklist.
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Design architecture docs for new features, refactors, or redesigns. Produces implementation-ready docs with complete file impact analysis.
Review architecture documents against code implementation and principles.
Orchestrate sequential documentation audits with checkpointing and resumption.
Guide sprint planning from scope assessment to spec artifacts.
| name | review-tests |
| description | Comprehensive test review using parallel test-reviewer agents. |
| disable-model-invocation | true |
Orchestrate a comprehensive test review using parallel test-reviewer agents.
Find all test files:
Glob: **/test_*.py, **/*_test.py
Map each test file to its source:
tests/test_foo.py → src/.../foo.pysrc/.../tests/test_bar.py → src/.../bar.pyReport: "Found N test files covering M source modules"
Group tests for parallel review. Options:
Default: By module (all tests for a source module → one agent)
For each group, launch test-reviewer agent:
Task(
subagent_type="test-reviewer",
prompt="Review tests.\n\ntest_path: {paths}\nsource_path: {paths}",
run_in_background=true
)
Launch ALL agents in a single message for true parallelism.
Wait for all agents to complete. Gather structured output.
Combine findings across all agents:
# Test Review Summary
## Overall
- Files reviewed: N
- Tests reviewed: N
- Remove: N | Improve: N | Add: N | Keep: N
## By Priority
### High (Remove - tests with no value)
[List across all files]
### Medium (Add - important gaps)
[List across all files]
### Low (Improve - existing tests to refine)
[List across all files]
## By Module
[Findings grouped by source module]
Based on findings, recommend: