# Perf Loop

> Iteratively optimize Fallow performance with stable benchmarks, before-and-after evidence, and correctness gates.

- Skill: `fallow-rs/perf-loop` (Agent Skill)
- Install (CLI): `npx skillmds@latest add fallow-rs/perf-loop`
- Raw SKILL.md: https://api.skillmd.com/api/skills/fallow-rs/perf-loop/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: fallow-rs (https://skillmd.com/u/fallow-rs)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/fallow-rs/perf-loop

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# Performance loop

1. Choose a stable benchmark and preserve its identity and workload.
2. Record a statistically useful baseline.
3. Profile the hot path before editing.
4. Implement one bounded optimization.
5. Re-run the same benchmark and correctness checks.
6. Keep the change only when the improvement is reproducible and no contract
   regresses.
7. Use a new benchmark identifier for a materially different workload.
8. Run `review`.

Do not report performance gains from debug builds or incomparable fixtures.