# peltier.io Spot cooling for hot paths. A profile-guided optimization agent that only ships wins it can prove. hotpath finds the 10–90% left on the floor between "the compiler" and "hire a perf consultant," with two properties no consultant offers: **verified equivalence** (a change provably preserves behavior or is discarded) and **self-verifying ROI** (the value claim is a stopwatch on trusted infrastructure, not a survey). Full design: **[SPEC.md](SPEC.md)**. ## Layout ``` crates/ Trust layer (agent has NO write access — SPEC §10) bench-runner/ Interleaved A/B timing, bootstrap CIs, A/A calibration diff-test/ Equivalence gates, corpus hash-pinning, per-target policy ledger/ Append-only SQLite attempt ledger (enforced by triggers) report/ ROI math: speedup CI → cores → dollars, caveats included agent/ Untrusted proposer (Claude Agent SDK, Python) playbook/ Optimization classes 1–7, tried strictly cheapest-first config/ accept.toml (thresholds), pricing.toml (ROI inputs) targets/ Per-target checkouts — the only agent-writable path corpora/ Hash-pinned golden-replay inputs (read-only to agent) results/ Calibration evidence, per-engagement outputs ``` ## Quick start ```sh cargo test --workspace # trust-layer unit tests just aa # A/A self-test: must yield a null verdict just compare "cmd-a" "cmd-b" # interleaved A/B with bootstrap CI ``` ## Status Phase 0 dry run in progress (see SPEC §5 for the phase plan and exit criteria). Two targets vendored and pinned (comrak 0.53.0, tokei 14.0.0); A/A calibration passed on both workloads; three attempts in the ledger — best so far **+4.6% [95% CI +3.3%, +5.8%]** on comrak via allocator swap, `needs-human-review` (sanitizer flag, analysis in `results/phase0/case-study-comrak.md`). Exit criteria (≥10% verified win) not yet met. Done: - Workspace with the four trust-layer crates; core statistics (interleaved scheduling, bootstrap ratio CIs, CI-lower-bound accept rule), append-only ledger schema with mutation-refusing triggers, corpus hash-pin verifier, equivalence-policy parser, ROI formulas — all unit-tested. - bench-runner CLI: whole-program `compare` and `aa` modes with env fingerprinting. - Playbook classes 1–7; agent tool contract and prompting spine. Next (Phase 1 exit criteria): - `perf stat` counters + max RSS + RAPL capture per run. - Automated A/A calibration sessions and regression-injection self-test recorded to `results/calibration/` (<5% FP, ≥95% detection). - diff-test orchestration end-to-end on two real targets; harness IPC for the agent tool surface. ## License GPL-3.0-or-later — see [LICENSE](LICENSE).