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Claude 4402775ed2 phase0: exit criteria met — tokei +10.4% median [8.5%, 12.0%] verified

Attempt 4 (phase0-tokei-002, class 3, ACCEPTED — first auto-accept):
every file was read through encoding_rs_io's DecodeReaderBytes via
generic read_to_end, which zero-fills every grown buffer chunk (~221MB
memset/run, 8.5% of Ir) and grows without a size hint. Patch: fs::read
with a BOM-gated fallback to the identical decode path (a UTF-8-BOM
file transcodes invalid sequences, so the fallback is required for
equivalence). Gates: golden byte-identical; differential fuzz old-vs-
new binaries 4,332 iterations (BOM grid, invalid UTF-8, binary junk,
randomized) zero divergence; 250 upstream tests green; ASan+LSan clean
with ASan-run output hashing to golden. Bench: +9.9% [8.0%, 12.7%].

Attempt 5 (phase0-tokei-003, ship tree, ACCEPTED): stacks fat LTO+cgu=1
(real +1.6% standalone but under threshold, phase0-tokei-001) on the
accepted patch; benched as a whole vs pristine: +10.4% [8.5%, 12.0%].
Median clears the Phase 0 exit bar; CI lower bound 8.5%.

Case study written (results/phase0/case-study-tokei.md), ledger at 5
attempts, CLAUDE.md phase line moved to Phase 1, next hypotheses
logged (tokei class-5 byte-skip table; comrak class-3 arena).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EcKPWQ3MQD4NdEHwar96u2

2026-07-06 19:57:05 +00:00

3.0 KiB

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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.

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

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 complete (see SPEC §5). Five attempts in the ledger across two pinned targets (comrak 0.53.0, tokei 14.0.0), A/A-calibrated, every number with CI and workload:

tokei +10.4% median [95% CI +8.5%, +12.0%] — read-path buffer zeroing eliminated + fat LTO, byte-identical, 4,332-iteration diff-fuzz clean, sanitizers clean, auto-accepted (results/phase0/case-study-tokei.md). Meets the Phase 0 exit bar.
comrak +4.6% [+3.3%, +5.8%] — mimalloc swap, needs-human-review on an LSan reachability flag (results/phase0/case-study-comrak.md).
Two null/sub-threshold results correctly rejected and logged.

Next: Phase 1 trust-layer hardening (containers, perf, automated calibration, gate orchestration, agent IPC).

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.