Step 10 · Demo
Try the method
Most agent benchmarks report a pass rate. This one separates three outcomes:
- verified pass — external check confirmed the change and the agent stayed in scope
- false completion — agent claimed done; verifier disagreed
- scope violation — agent edited a forbidden file
Run it
git clone https://github.com/camerontjs-dot/verified-done cd verified-done python3 runner/run.py list python3 runner/run.py selftest
selftest proves every verifier discriminates (start fails, solution passes). Latest public summary: 8/8 tasks discriminate; scope detection fires correctly.
Two splits
Headline numbers from the private sealed lab are cited, not shipped. The demo tasks here were authored fresh so the method is inspectable without burning held-out fixtures.
Scrubbed live evidence (verify-tool ablation): LIVE_EVIDENCE.md (Findings A–F).
What the live evidence shows
- A (Haiku): same model,
run_verifyoff → 3/3 false completion; on → 3/3 clean. - D/E (local coder-14b): n=10 per arm, pooled across two Ollama runtimes: 20/20 false completions without the tool, 1/20 with it. The n=2 row is superseded.
- C (local qwen3.5:9b): withdrawn as a control. The old “abstained either way” label was a timeout, then a harness bug that discarded reasoning.
- F (local qwen3:14b): the actual model-dependence cell. 10/10 FC without the tool, 9/10 with it, after the adapter fix.
Not a model leaderboard. Eight tasks is a demonstration of the scoring contract. Live local arms are exploratory; n=10 per cell, not n=2.