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
The agent's only door to the trust layer (SPEC 3.5, 10): harnessd
serves read_profile, read_ledger, read_playbook, read_target_source,
propose_patch, run_verdict over stdio JSON lines. propose_patch
enforces the path allowlist (relative paths only, no parent
components, no .git, target name validated) before git apply --check
+ apply rooted in the target workspace; run_verdict builds the
candidate into an isolated dir and hands off to the verdict pipeline
(pristine-rebuilt baseline included). Python client
(agent/hotpath_agent/harness.py) + tools.py rewired from stubs to
live calls.
E2E evidence: escape attempts refused (bad target name, ../ paths,
trust-layer diff touching config/accept.toml rejected before any
apply); benign doc patch applied, candidate built, full verdict ran
mechanically end to end -> +8.9% [1.079, 1.104] accepted (ship-tree
patches ride along as the candidate), ledger row phase1-ipc-smoke-001.
Phase 1 caveat recorded in the daemon header: same-uid filesystem
read-only enforcement still needs the separate-user/container setup.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01EcKPWQ3MQD4NdEHwar96u2
Claude