Reproduce it yourself

Nothing here is a screenshot. Every number regenerates from a pinned corpus through the same commands.

Prerequisites

  • A Linux/POSIX host. The pipeline is Unix-only at runtime: harnessd (Unix sockets, setsid), service mode, the isolation wrapper, and every sh-based gate assume it. Windows compiles the workspace and runs the portable unit tests, but cannot run the pipeline.
  • Rust (stable) + just; clang/cmake for the C target; valgrind for callgrind profiling. Nightly Rust for the sanitizer gate.
  • Targets are vendored fresh (their workspace/ is gitignored); each targets/<name>/target.toml has the [fetch] recipe.

The commands

just build / test / lint       # trust-layer workspace
just aa [cmd]                  # A/A self-test — must be a null verdict
just calibrate <cmd> <out>     # A/A false-positive + injection detection
just gates <target>            # corpus pin + upstream tests + golden replay
just verdict <t> <bin> ...     # gates + bench vs pristine baseline + ledger row
just report <run-id>           # ROI report from a ledger row

just gates does not fuzz. Differential fuzz differs the candidate against a pristine baseline, and only just verdict builds one — so on the gates flow the fuzz layer reports Skipped, with the reason recorded, rather than comparing the candidate against itself. Use gates as a fast equivalence check; the fuzz gate (and the sanitizer lanes) run on the accept path, where an accept is impossible without a passed fuzz gate.

Service mode (Phase 4):

just service <baseline-bin> <candidate-bin> <doc>     # interleaved p50/p99 CIs
just service-calibrate <server> <doc> <out>           # latency A/A + injection
just report <run-id> --service-json <json>            # latency + ROI report

The agent loop, behind OS isolation:

just isolation-check                    # 19 boundary checks, both modes
scripts/agent-isolated.sh <target> <run-id>   # one unattended attempt, confined

Auditing a result

Every accepted win can be re-audited independently:

python3 scripts/audit-attempt.py <run-id>        # mechanical re-check
python3 scripts/diff-fuzz-<target>.py <dir> 10000 <baseline-bin> <candidate-bin>

The ledger itself is the record: results/ledger.sqlite, append-only, every attempt (win or loss) with its hypothesis, gates, bench evidence, and verdict.

Use it on your own code

The whole discipline is installable into any repo as an Agent Skill, driven from any SKILL.md-reading harness — see Consume it: the peltier skill.