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SKILLS/25-algorithms-performance.md

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+# Algorithms & Performance
+
+Use this skill when performance matters (large inputs, hot paths, or repeated calls).
+
+## Checklist
+- Identify the **state** you’re recomputing.
+- Add **memoization / caching** when the same subproblem repeats.
+- Prefer **linear scans** + caches over nested loops when possible.
+- If you can write it as a **recurrence**, you can test it.
+
+## Practical heuristics
+- Measure first when possible (timing + input sizes).
+- Optimize the biggest wins: avoid repeated I/O, repeated parsing, repeated network calls.
+- Keep caches bounded (size/TTL) and invalidate safely.
+- Choose data structures intentionally: dict/set for membership, heap for top-k, deque for queues.
+
+## Review notes (for PRs)
+- Call out accidental O(n²) patterns.
+- Suggest table/DP or memoization when repeated work is obvious.
+- Add tests that cover base cases + typical cases + worst-case size.