chore: import upstream snapshot with attribution
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applyTo: "**"
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excludeAgent: ["coding-agent"]
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# Code Review Instructions
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## Knowledge Cutoff
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Your training data has a cutoff. Treat anything you don't recognize as **new, not wrong**. Here are things you might flag as incorrect but are actually valid:
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- Model names (e.g., `gpt-5`)
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- GitHub runner types (e.g., `ubuntu-slim`)
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## Comment Format (MANDATORY)
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Every comment MUST use this exact format: `<emoji> **<severity>:** <description>`
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| Severity | Emoji |
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| -------- | ----- |
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| CRITICAL | 🔴 |
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| MODERATE | 🟡 |
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| NIT | 🟢 |
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Examples:
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- 🔴 **CRITICAL:** User input is passed directly into the SQL query without parameterization — SQL injection risk. Use a parameterized query instead.
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- 🟡 **MODERATE:** This loops over each item and issues a separate query — N+1 problem. Use a single batch query or a join.
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- 🟢 **NIT:** This nested `if/elif/else` is hard to follow. Consider using early returns to flatten the structure.
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## Do NOT Comment On
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- Future dates, version numbers, model names, or runner types — your knowledge cutoff makes these unreliable
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- Discrepancies between PR description and code — focus on the code
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- Naming style preferences — only flag actively misleading names
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- Hypothetical or unlikely edge cases — if you'd write "while unlikely", "could potentially", or "edge case where", skip it. Only flag issues that realistically occur in practice.
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applyTo: ".github/workflows/**/*.yml"
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---
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# GitHub Actions Code Review Instructions
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For workflow style conventions, see [.claude/rules/github-actions.md](../../.claude/rules/github-actions.md).
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---
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applyTo: "**/*.py"
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---
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# Python Code Review Instructions
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For style conventions and code examples, see [.claude/rules/python.md](../../.claude/rules/python.md).
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