AI Review Bot
47 lines
2.2 KiB
Markdown
47 lines
2.2 KiB
Markdown
---
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name: triage-findings
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description: Merge code-review findings, sort and renumber them by severity, resolve real issues, and move false positives into exclusions.
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---
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# Triage Findings
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## When To Use
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Use this skill when you receive multiple review findings, screenshots, comments, or issue lists that need to become one final triaged list.
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It is also used when some findings are false positives and should be moved into the exclusions list.
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## Workflow
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1. Collect all findings into one list.
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2. Merge duplicates into a single finding when they describe the same issue.
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3. Sort the final list by severity:
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- critical
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- warning
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- info
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4. Renumber the sorted list from 1 upward.
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5. Rewrite each finding concisely so the final list reads cleanly and consistently.
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6. If a finding is a false positive, do not keep it in the final list.
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7. Add false positives to the exclusions list as a top-level JSON array in `.gitea/ai-review/exclusions.json`, and preserve the original finding wording as much as possible, including language and semantics. Do not wrap the array in `exclusions` or `excluded_findings`.
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## Resolution Flow
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After the list is merged and ordered, resolve the remaining findings one by one.
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1. Start from the highest severity item.
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2. Identify the root cause in the relevant file or context.
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3. Apply the smallest safe change that fixes the issue.
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4. Add or update tests when behavior changes.
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5. Re-check the issue after the change.
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6. If the item is confirmed false positive, move it to exclusions instead of changing code.
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7. Continue until the list is either fixed or explicitly excluded.
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## Output Rules
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- Keep the final findings list in severity order, then by any stable secondary order needed to make it readable.
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- Keep numbering contiguous after filtering and merging.
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- Preserve useful details like file path, location, and suggested fix.
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- Keep exclusions entries minimal and consistent with the project schema.
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- When writing exclusions, always output a top-level JSON array.
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- When writing exclusions, prefer the original issue text and language; only paraphrase if needed to fit the schema.
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- If the source already provides a severity or title, keep it unless it conflicts with the final ordering.
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