- bench-runner service mode (SPEC §3.1 mode c): a coordinated-omission-
correct, open-loop, fixed-rate load generator; latency measured from
the intended send time so queueing is counted, not hidden. Interleaved
A/B of two server binaries, exact percentiles (bounded sample, no HDR
bucketing error), bootstrap p50/p99 CIs via the existing ratio-CI
machine. service-calibrate: A/A false-positive + injected latency-
regression detection (calibration in progress).
- targets/cjson/service.c: minimal single-threaded HTTP server wrapping
the patched cJSON.c (trust-layer, outside the workspace allowlist);
env-toggled per-request busy-wait for the injection calibration only.
- report generator (crates/report bin): reads a ledger row +
optional service-latency JSON, renders throughput→cores→dollars and/or
latency percentiles, every figure with its CI, pricing source, and the
methodology printed inline (SPEC §9); flags any non-accepted row so a
rejected change never reads as a committed saving.
- ledger::report_row; justfile service/service-calibrate/report.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EcKPWQ3MQD4NdEHwar96u2
Closes the CI-reachable slice of the Phase 1 infra gaps:
- trust-layer job: cargo test + clippy -D warnings + fmt
- target-gates-no-net: fetches pinned targets (new targets/fetch.sh),
regenerates + verifies corpora, runs 'just gates tokei'
mechanically, and executes the bench workload inside a
--network=none container (SPEC 3.1/10 no-net requirement)
- runner-calibration (informational): A/A + injection harness measures
the shared runner's noise floor per run, evidence uploaded as an
artifact — environments are judged empirically, not assumed
- perf-probe (informational): reports which perf event sources work
docs/infra.md maps each remaining hardware requirement (pinned cores,
governor/SMT control, separate-uid trust layer) to the bench-metal
self-hosted runner setup a human can complete in ~15 min.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EcKPWQ3MQD4NdEHwar96u2
Adds 'bench-runner calibrate': N A/A sessions counted against a <5%
false-positive bar, and N sessions with a synthetic slowdown injected
as a real busy-wait inside the candidate's timed window, counted
against a >=95% detection bar (detected = ratio CI entirely below 1.0).
Bootstrap seed varies per session so resampling noise is not
correlated across the very statistic being validated. JSON evidence
includes per-session CIs, injected wait, acceptance verdict, and env
fingerprint.
First run against the real comrak workload (20+20 sessions, pinned
core): false-positive rate 0.000, detection rate 0.950 -> PASS.
Evidence: results/calibration/2026-07-06-comrak-full-calibration.json.
Closes the SPEC 3.1 acceptance-criteria gap; remaining Phase 1 gaps:
no-net containers, perf profiling, diff-test orchestration, agent IPC.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EcKPWQ3MQD4NdEHwar96u2
Commit the spec and scaffold the system it describes:
- SPEC.md: the full v0.1 engineering spec
- crates/: trust-layer Rust workspace, unit-tested
- bench-runner: interleaved ABAB scheduling with discarded warm-ups,
deterministic bootstrap CIs over the ratio of medians,
CI-lower-bound accept rule, env fingerprinting, and a CLI with
compare + A/A self-test modes (A/A verified passing end-to-end)
- diff-test: gate outcome model, sha256 corpus pin verifier that
refuses on mismatch, per-target equivalence policy parser
(byte-identical default, explicit fp-tolerance opt-in)
- ledger: append-only SQLite attempt schema with UPDATE/DELETE
refused by triggers, anti-double-attempt query
- report: cores-saved and dollars/yr ROI math over speedup CIs,
pricing.toml inputs
- playbook/: classes 1-7 with preconditions, procedure, verification
notes, and known failure modes per class
- agent/: Python package skeleton — six-tool contract and prompting
spine, harness IPC deferred to Phase 1
- config/: accept.toml (2% threshold, 30 runs/side), pricing.toml
- targets/, corpora/, results/calibration/: layout and policy docs
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EcKPWQ3MQD4NdEHwar96u2
Claude