review-feedback-schema

# Review Feedback Schema

## Purpose

Structured format for logging code review outcomes. This data enables:
1. Identifying rules that produce false positives
2. Tracking skill accuracy over time
3. Automated skill improvement via pattern analysis

## Schema

```csv
date,file,line,rule_source,category,severity,issue,verdict,rationale
```

| Field | Type | Description | Example Values |
|-------|------|-------------|----------------|
| `date` | ISO date | When review occurred | `2025-12-23` |
| `file` | path | Relative file path | `amelia/agents/developer.py` |
| `line` | string | Line number(s) | `128`, `190-191` |
| `rule_source` | string | Skill and rule that triggered issue | `python-code-review/common-mistakes:unused-variables`, `pydantic-ai-common-pitfalls:tool-decorator` |
| `category` | enum | Issue taxonomy | `type-safety`, `async`, `error-handling`, `style`, `patterns`, `testing`, `security` |
| `severity` | enum | As flagged by reviewer | `critical`, `major`, `minor` |
| `issue` | string | Brief description | `Return type list[Any] loses type safety` |
| `verdict` | enum | Human decision | `ACCEPT`, `REJECT`, `DEFER`, `ACKNOWLEDGE` |
| `rationale` | string | Why verdict was chosen | `pydantic-ai docs explicitly support this pattern` |

## Verdict Types

| Verdict | Meaning | Action |
|---------|---------|--------|
| `ACCEPT` | Issue is valid, will fix | Code change made |
| `REJECT` | Issue is invalid/wrong | No change; may improve skill |
| `DEFER` | Valid but not fixing now | Tracked for later |
| `ACKNOWLEDGE` | Valid but intentional | Document why it's intentional |

### When to Use Each

**ACCEPT**: The reviewer correctly identified a real issue.
```csv
2025-12-27,amelia/agents/developer.py,128,python-code-review:type-safety,type-safety,major,Return type list[Any] loses type safety,ACCEPT,Changed to list[AgentMessage]
```

**REJECT**: The reviewer was wrong - the code is correct.
```csv
2025-12-23,amelia/drivers/api/openai.py,102,python-code-review:li