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T

Claude 5d6c259b30 docs: full mdBook site + GitHub Pages deploy; rewrite README as project front page

- docs/: an mdBook documentation site — thesis, architecture, measurement
  discipline, equivalence gates, agent loop, isolation/anti-reward-hacking,
  playbook, ROI, reproduce, roadmap, and the five case studies (pulled from
  their single source in results/ via {{#include}}). Builds clean (21
  pages).
- .github/workflows/docs.yml: builds mdBook and deploys to GitHub Pages on
  push to main (one-time setup: Settings → Pages → Source = GitHub Actions).
- README.md: rewritten as the project front page — the thesis, the verified
  results table, layout, quick start, how it stays honest, links to the
  book. Replaces the stale Phase-0-era text.

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

2026-07-12 00:20:20 +00:00

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Reproduce it yourself

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

Prerequisites

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

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 <candidate-bin>   # 10k fuzz

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

1.7 KiB Raw Blame History

Reproduce it yourself

Prerequisites

The commands

Auditing a result

1.7 KiB

Raw Blame History