The Claude Agent SDK loop (agent/hotpath_agent/loop.py, model
claude-fable-5) drives the seven harness tools over a standalone stdio
MCP server (mcp_server.py) and runs the full profile -> hypothesize ->
patch -> gated-verdict cycle on comrak with no human in the loop.
Three audited attempts, all honest rejections, ZERO false accepts:
- phase2-comrak-001 class 3: syntect buffer with_capacity, [0.971,1.007]
- phase2-comrak-002 class 5: gate dead VecDeque build, [0.982,1.026]
- phase2-comrak-003 class 6: hoist find_special_char check, [0.970,1.007]
The agent picked the cheapest untried class each time (3->5->6) and
TWICE refused to fabricate a verdict it couldn't read back, verifying
ledger integrity instead — the anti-reward-hacking behavior SPEC §10
targets.
Harness changes surfaced by the loop:
- run_verdict is now async: launches the multi-minute build+bench
detached (past the 60s MCP transport cap) and returns immediately;
new read_verdict op polls the append-only ledger row (ledger
verdict_summary). Fixes attempt 001's unreadable-verdict gap.
- read_target_source takes offset/limit line windows so 100KB+ files
page instead of overflowing — removes the agent's reason to reach for
a shell (attempt 003 paged a 2400-line file cleanly, no shell).
Honest boundary note (case study + code comments): in THIS dev
container the SDK tool allow/deny layer is defense-in-depth, not the
trust boundary — a nested CLI as root under a parent session doesn't
reliably gate built-ins. SPEC §10's boundary is OS process/user
isolation; that hardening is the remaining Phase 2 exit item
(docs/infra.md). What holds regardless: propose_patch is the only
mediated write path (path-allowlist + git apply) and the ledger is
append-only.
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