[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6CC2DF338WSWMQ6JYFVS4SK":3,"skill-same:01M6CC2DF338WSWMQ6JYFVS4SK":68},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":22,"publishedAt":36,"linkOnly":37,"markdownContent":38,"markdownBody":39,"frontMatter":40,"refName":41,"commitSha":42,"skillDirectory":43,"forksCount":44,"repositoryHtmlUrl":45,"repositoryHomepageUrl":6,"ownerHtmlUrl":46,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":47,"install":48,"resources":61},"01M6CC2DF338WSWMQ6JYFVS4SK","review-feedback-schema",null,"Schema for tracking code review outcomes to enable feedback-driven skill improvement. Use when logging review results or analyzing review quality.","ray-manaloto\u002Fmacos-development-environment","ray-manaloto","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F227192835?v=4","01M6CBR7J13ZA01X5YB1A1QRJP","01M6CBR7P0S3NS8ZV81JYNST14",1,"MIT","https:\u002F\u002Fgithub.com\u002Fray-manaloto\u002Fmacos-development-environment\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fskills\u002Freview-feedback-schema\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000007","代码审查","SCENARIO","使用场景",[23,24,25,26,27,28,29,30,31,32,33,34,35],"review","feedback","schema","review feedback schema","code review","code","logging","analyzing","quality","results","tracking","use","outcomes","2026-11-10 10:12:30",false,"---\nname: review-feedback-schema\ndescription: Schema for tracking code review outcomes to enable feedback-driven skill improvement. Use when logging review results or analyzing review quality.\n---\n\n# Review Feedback Schema\n\n## Purpose\n\nStructured format for logging code review outcomes. This data enables:\n1. Identifying rules that produce false positives\n2. Tracking skill accuracy over time\n3. Automated skill improvement via pattern analysis\n\n## Schema\n\n```csv\ndate,file,line,rule_source,category,severity,issue,verdict,rationale\n```\n\n| Field | Type | Description | Example Values |\n|-------|------|-------------|----------------|\n| `date` | ISO date | When review occurred | `2025-12-23` |\n| `file` | path | Relative file path | `amelia\u002Fagents\u002Fdeveloper.py` |\n| `line` | string | Line number(s) | `128`, `190-191` |\n| `rule_source` | string | Skill and rule that triggered issue | `python-code-review\u002Fcommon-mistakes:unused-variables`, `pydantic-ai-common-pitfalls:tool-decorator` |\n| `category` | enum | Issue taxonomy | `type-safety`, `async`, `error-handling`, `style`, `patterns`, `testing`, `security` |\n| `severity` | enum | As flagged by reviewer | `critical`, `major`, `minor` |\n| `issue` | string | Brief description | `Return type list[Any] loses type safety` |\n| `verdict` | enum | Human decision | `ACCEPT`, `REJECT`, `DEFER`, `ACKNOWLEDGE` |\n| `rationale` | string | Why verdict was chosen | `pydantic-ai docs explicitly support this pattern` |\n\n## Verdict Types\n\n| Verdict | Meaning | Action |\n|---------|---------|--------|\n| `ACCEPT` | Issue is valid, will fix | Code change made |\n| `REJECT` | Issue is invalid\u002Fwrong | No change; may improve skill |\n| `DEFER` | Valid but not fixing now | Tracked for later |\n| `ACKNOWLEDGE` | Valid but intentional | Document why it's intentional |\n\n### When to Use Each\n\n**ACCEPT**: The reviewer correctly identified a real issue.\n```csv\n2025-12-27,amelia\u002Fagents\u002Fdeveloper.py,128,python-code-review:type-safety,type-safety,major,Return type list[Any] loses type safety,ACCEPT,Changed to list[AgentMessage]\n```\n\n**REJECT**: The reviewer was wrong - the code is correct.\n```csv\n2025-12-23,amelia\u002Fdrivers\u002Fapi\u002Fopenai.py,102,python-code-review:line-length,style,minor,Line too long (104 > 100),REJECT,ruff check passes - no E501 violation exists\n```\n\n**DEFER**: Valid issue but out of scope for current work.\n```csv\n2025-12-22,api\u002Fhandlers.py,45,fastapi-code-review:error-handling,error-handling,minor,Missing specific exception type,DEFER,Refactoring planned for Q1\n```\n\n**ACKNOWLEDGE**: Intentional design decision.\n```csv\n2025-12-21,core\u002Fcache.py,89,python-code-review:optimization,patterns,minor,Using dict instead of dataclass,ACKNOWLEDGE,Performance-critical path - intentional\n```\n\n## Rule Source Format\n\nFormat: `skill-name\u002Fsection:rule-id` or `skill-name:rule-id`\n\nExamples:\n- `python-code-review\u002Fcommon-mistakes:unused-variables`\n- `pydantic-ai-common-pitfalls:tool-decorator`\n- `fastapi-code-review:dependency-injection`\n- `pytest-code-review:fixture-scope`\n\nUse the skill folder name and identify the specific rule or section that triggered the issue.\n\n## Category Taxonomy\n\n| Category | Description | Examples |\n|----------|-------------|----------|\n| `type-safety` | Type annotation issues | Missing types, incorrect types, `Any` usage |\n| `async` | Async\u002Fawait issues | Blocking in async, missing await |\n| `error-handling` | Exception handling | Bare except, missing error handling |\n| `style` | Code style\u002Fformatting | Line length, naming conventions |\n| `patterns` | Design patterns | Anti-patterns, framework misuse |\n| `testing` | Test quality | Missing coverage, flaky tests |\n| `security` | Security issues | Injection, secrets exposure |\n\n## Writing Good Rationales\n\n### For ACCEPT\n\nExplain what you fixed:\n- \"Changed Exception to (FileNotFoundError, OSError)\"\n- \"Fixed using model_copy(update={...})\"\n- \"Removed unused Any import\"\n\n### For REJECT\n\nExplain why the issue is invalid:\n- \"ruff check passes - no E501 violation exists\" (linter authoritative)\n- \"pydantic-ai docs explicitly support this pattern\" (framework idiom)\n- \"Intentional optimization documented in code comment\" (documented decision)\n\n### For DEFER\n\nExplain when\u002Fwhy it will be addressed:\n- \"Tracked in issue #123\"\n- \"Refactoring planned for Q1\"\n- \"Blocked on dependency upgrade\"\n\n### For ACKNOWLEDGE\n\nExplain why it's intentional:\n- \"Performance-critical path per CLAUDE.md\"\n- \"Legacy API compatibility requirement\"\n- \"Matches upstream library pattern\"\n\n## Example Log\n\n```csv\ndate,file,line,rule_source,category,severity,issue,verdict,rationale\n2025-12-20,tests\u002Fintegration\u002Ftest_cli_flows.py,407,pytest-code-review:parametrization,testing,minor,Unused extra_args parameter in parametrization,ACCEPT,Fixed - removed dead parameter\n2025-12-20,tests\u002Fintegration\u002Ftest_cli_flows.py,237-242,pytest-code-review:coverage,testing,major,Missing review --local in git repo error test,REJECT,Not applicable - review uses different error path\n2025-12-21,amelia\u002Fserver\u002Forchestrator\u002Fservice.py,1702,python-code-review:immutability,patterns,critical,Direct mutation of frozen ExecutionState,ACCEPT,Fixed using model_copy(update={...})\n2025-12-23,amelia\u002Fdrivers\u002Fapi\u002Ftools.py,48-53,pydantic-ai-common-pitfalls:tool-decorator,patterns,major,Misleading RunContext pattern - should use decorators,REJECT,pydantic-ai docs explicitly support passing raw functions with RunContext to Agent(tools=[])\n2025-12-23,amelia\u002Fdrivers\u002Fapi\u002Fopenai.py,102,python-code-review:line-length,style,minor,Line too long (104 > 100),REJECT,ruff check passes - no E501 violation exists\n2025-12-27,amelia\u002Fcore\u002Forchestrator.py,190-191,python-code-review:exception-handling,error-handling,major,Generic exception handling in get_code_changes_for_review,ACCEPT,Changed Exception to (FileNotFoundError OSError)\n2025-12-27,amelia\u002Fagents\u002Fdeveloper.py,128,python-code-review:type-safety,type-safety,major,Return type list[Any] loses type safety,ACCEPT,Changed to list[AgentMessage] and removed unused Any import\n```\n\n## Pre-Review Verification Checklist\n\nBefore reporting ANY finding, reviewers MUST verify:\n\n### Verification Steps\n\n1. **Confirm the issue exists**: Read the actual code, don't infer from context\n2. **Check surrounding code**: The issue may be handled elsewhere (guards, earlier checks)\n3. **Trace state\u002Fvariable usage**: Search for all references before claiming \"unused\"\n4. **Verify assertions**: If claiming \"X is missing\", confirm X isn't present\n5. **Check framework handling**: Many frameworks handle validation\u002Ferrors automatically\n6. **Validate syntax understanding**: Verify against current docs (Tailwind v4, TS 5.x, etc.)\n\n### Common False Positive Patterns\n\n| Pattern | Root Cause | Prevention |\n|---------|------------|------------|\n| \"Unused variable\" | Variable used elsewhere | Search all references |\n| \"Missing validation\" | Framework validates | Check Pydantic\u002FZod\u002Fetc. |\n| \"Type assertion\" | Actually annotation | Confirm `as` vs `:` |\n| \"Memory leak\" | Cleanup exists | Check effect returns |\n| \"Wrong syntax\" | New framework version | Verify against current docs |\n| \"Style issue\" | Preference not rule | Both approaches valid |\n\n### Signals of False Positive Risk\n\nIf you're about to flag any of these, double-check:\n- \"This variable appears unused\" → Search for ALL references first\n- \"Missing error handling\" → Check parent\u002Fframework handling\n- \"Should use X instead of Y\" → Both may be valid\n- \"This syntax looks wrong\" → Verify against current version docs\n\nReference: [review-verification-protocol](..\u002Freview-verification-protocol\u002FSKILL.md) for full verification workflow.\n\n## How This Feeds Into Skill Improvement\n\n1. **Aggregate by rule_source**: Identify which rules have high REJECT rates\n2. **Analyze rationales**: Find common themes in rejections\n3. **Update skills**: Add exceptions, clarifications, or verification steps\n4. **Track impact**: Measure if changes reduce rejection rate\n\nSee `review-skill-improver` skill for the full analysis workflow.\n\n### Improvement Signals\n\n| Pattern | Skill Improvement |\n|---------|-------------------|\n| \"linter passes\" rejections | Add linter verification step before flagging style issues |\n| \"docs support this\" rejections | Add exception for documented framework patterns |\n| \"intentional\" rejections | Add codebase context check before flagging |\n| \"wrong code path\" rejections | Add code tracing step before claiming gaps |\n","# Review Feedback Schema\n\n## Purpose\n\nStructured format for logging code review outcomes. This data enables:\n1. Identifying rules that produce false positives\n2. Tracking skill accuracy over time\n3. Automated skill improvement via pattern analysis\n\n## Schema\n\n```csv\ndate,file,line,rule_source,category,severity,issue,verdict,rationale\n```\n\n| Field | Type | Description | Example Values |\n|-------|------|-------------|----------------|\n| `date` | ISO date | When review occurred | `2025-12-23` |\n| `file` | path | Relative file path | `amelia\u002Fagents\u002Fdeveloper.py` |\n| `line` | string | Line number(s) | `128`, `190-191` |\n| `rule_source` | string | Skill and rule that triggered issue | `python-code-review\u002Fcommon-mistakes:unused-variables`, `pydantic-ai-common-pitfalls:tool-decorator` |\n| `category` | enum | Issue taxonomy | `type-safety`, `async`, `error-handling`, `style`, `patterns`, `testing`, `security` |\n| `severity` | enum | As flagged by reviewer | `critical`, `major`, `minor` |\n| `issue` | string | Brief description | `Return type list[Any] loses type safety` |\n| `verdict` | enum | Human decision | `ACCEPT`, `REJECT`, `DEFER`, `ACKNOWLEDGE` |\n| `rationale` | string | Why verdict was chosen | `pydantic-ai docs explicitly support this pattern` |\n\n## Verdict Types\n\n| Verdict | Meaning | Action |\n|---------|---------|--------|\n| `ACCEPT` | Issue is valid, will fix | Code change made |\n| `REJECT` | Issue is invalid\u002Fwrong | No change; may improve skill |\n| `DEFER` | Valid but not fixing now | Tracked for later |\n| `ACKNOWLEDGE` | Valid but intentional | Document why it's intentional |\n\n### When to Use Each\n\n**ACCEPT**: The reviewer correctly identified a real issue.\n```csv\n2025-12-27,amelia\u002Fagents\u002Fdeveloper.py,128,python-code-review:type-safety,type-safety,major,Return type list[Any] loses type safety,ACCEPT,Changed to list[AgentMessage]\n```\n\n**REJECT**: The reviewer was wrong - the code is correct.\n```csv\n2025-12-23,amelia\u002Fdrivers\u002Fapi\u002Fopenai.py,102,python-code-review:line-length,style,minor,Line too long (104 > 100),REJECT,ruff check passes - no E501 violation exists\n```\n\n**DEFER**: Valid issue but out of scope for current work.\n```csv\n2025-12-22,api\u002Fhandlers.py,45,fastapi-code-review:error-handling,error-handling,minor,Missing specific exception type,DEFER,Refactoring planned for Q1\n```\n\n**ACKNOWLEDGE**: Intentional design decision.\n```csv\n2025-12-21,core\u002Fcache.py,89,python-code-review:optimization,patterns,minor,Using dict instead of dataclass,ACKNOWLEDGE,Performance-critical path - intentional\n```\n\n## Rule Source Format\n\nFormat: `skill-name\u002Fsection:rule-id` or `skill-name:rule-id`\n\nExamples:\n- `python-code-review\u002Fcommon-mistakes:unused-variables`\n- `pydantic-ai-common-pitfalls:tool-decorator`\n- `fastapi-code-review:dependency-injection`\n- `pytest-code-review:fixture-scope`\n\nUse the skill folder name and identify the specific rule or section that triggered the issue.\n\n## Category Taxonomy\n\n| Category | Description | Examples |\n|----------|-------------|----------|\n| `type-safety` | Type annotation issues | Missing types, incorrect types, `Any` usage |\n| `async` | Async\u002Fawait issues | Blocking in async, missing await |\n| `error-handling` | Exception handling | Bare except, missing error handling |\n| `style` | Code style\u002Fformatting | Line length, naming conventions |\n| `patterns` | Design patterns | Anti-patterns, framework misuse |\n| `testing` | Test quality | Missing coverage, flaky tests |\n| `security` | Security issues | Injection, secrets exposure |\n\n## Writing Good Rationales\n\n### For ACCEPT\n\nExplain what you fixed:\n- \"Changed Exception to (FileNotFoundError, OSError)\"\n- \"Fixed using model_copy(update={...})\"\n- \"Removed unused Any import\"\n\n### For REJECT\n\nExplain why the issue is invalid:\n- \"ruff check passes - no E501 violation exists\" (linter authoritative)\n- \"pydantic-ai docs explicitly support this pattern\" (framework idiom)\n- \"Intentional optimization documented in code comment\" (documented decision)\n\n### For DEFER\n\nExplain when\u002Fwhy it will be addressed:\n- \"Tracked in issue #123\"\n- \"Refactoring planned for Q1\"\n- \"Blocked on dependency upgrade\"\n\n### For ACKNOWLEDGE\n\nExplain why it's intentional:\n- \"Performance-critical path per CLAUDE.md\"\n- \"Legacy API compatibility requirement\"\n- \"Matches upstream library pattern\"\n\n## Example Log\n\n```csv\ndate,file,line,rule_source,category,severity,issue,verdict,rationale\n2025-12-20,tests\u002Fintegration\u002Ftest_cli_flows.py,407,pytest-code-review:parametrization,testing,minor,Unused extra_args parameter in parametrization,ACCEPT,Fixed - removed dead parameter\n2025-12-20,tests\u002Fintegration\u002Ftest_cli_flows.py,237-242,pytest-code-review:coverage,testing,major,Missing review --local in git repo error test,REJECT,Not applicable - review uses different error path\n2025-12-21,amelia\u002Fserver\u002Forchestrator\u002Fservice.py,1702,python-code-review:immutability,patterns,critical,Direct mutation of frozen ExecutionState,ACCEPT,Fixed using model_copy(update={...})\n2025-12-23,amelia\u002Fdrivers\u002Fapi\u002Ftools.py,48-53,pydantic-ai-common-pitfalls:tool-decorator,patterns,major,Misleading RunContext pattern - should use decorators,REJECT,pydantic-ai docs explicitly support passing raw functions with RunContext to Agent(tools=[])\n2025-12-23,amelia\u002Fdrivers\u002Fapi\u002Fopenai.py,102,python-code-review:line-length,style,minor,Line too long (104 > 100),REJECT,ruff check passes - no E501 violation exists\n2025-12-27,amelia\u002Fcore\u002Forchestrator.py,190-191,python-code-review:exception-handling,error-handling,major,Generic exception handling in get_code_changes_for_review,ACCEPT,Changed Exception to (FileNotFoundError OSError)\n2025-12-27,amelia\u002Fagents\u002Fdeveloper.py,128,python-code-review:type-safety,type-safety,major,Return type list[Any] loses type safety,ACCEPT,Changed to list[AgentMessage] and removed unused Any import\n```\n\n## Pre-Review Verification Checklist\n\nBefore reporting ANY finding, reviewers MUST verify:\n\n### Verification Steps\n\n1. **Confirm the issue exists**: Read the actual code, don't infer from context\n2. **Check surrounding code**: The issue may be handled elsewhere (guards, earlier checks)\n3. **Trace state\u002Fvariable usage**: Search for all references before claiming \"unused\"\n4. **Verify assertions**: If claiming \"X is missing\", confirm X isn't present\n5. **Check framework handling**: Many frameworks handle validation\u002Ferrors automatically\n6. **Validate syntax understanding**: Verify against current docs (Tailwind v4, TS 5.x, etc.)\n\n### Common False Positive Patterns\n\n| Pattern | Root Cause | Prevention |\n|---------|------------|------------|\n| \"Unused variable\" | Variable used elsewhere | Search all references |\n| \"Missing validation\" | Framework validates | Check Pydantic\u002FZod\u002Fetc. |\n| \"Type assertion\" | Actually annotation | Confirm `as` vs `:` |\n| \"Memory leak\" | Cleanup exists | Check effect returns |\n| \"Wrong syntax\" | New framework version | Verify against current docs |\n| \"Style issue\" | Preference not rule | Both approaches valid |\n\n### Signals of False Positive Risk\n\nIf you're about to flag any of these, double-check:\n- \"This variable appears unused\" → Search for ALL references first\n- \"Missing error handling\" → Check parent\u002Fframework handling\n- \"Should use X instead of Y\" → Both may be valid\n- \"This syntax looks wrong\" → Verify against current version docs\n\nReference: [review-verification-protocol](..\u002Freview-verification-protocol\u002FSKILL.md) for full verification workflow.\n\n## How This Feeds Into Skill Improvement\n\n1. **Aggregate by rule_source**: Identify which rules have high REJECT rates\n2. **Analyze rationales**: Find common themes in rejections\n3. **Update skills**: Add exceptions, clarifications, or verification steps\n4. **Track impact**: Measure if changes reduce rejection rate\n\nSee 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sources\", \"summarize evidence\", \"write a deep review\", or mentions evidence synthesis, finding consolidation, cross-source analysis, or research summarization.","https:\u002F\u002Fgithub.com\u002Fray-manaloto\u002Fmacos-development-environment\u002Fblob\u002Fmain\u002Frsm-subagents\u002Fplugins\u002Fresearch-review-toolkit\u002Fskills\u002Fevidence-synthesis\u002FSKILL.md",[163],{"categoryNo":131,"categoryName":132,"taxonomyType":20,"taxonomyTypeDesc":21},[165,115,166,119,98,167,168,169,83,170,23],"evidence synthesis","evidence","deep review","analysis","write","reference"]