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Benchmark adoption

Adopt an upstream benchmark into a BenchFlow benchmark with bench eval adopt.

What the router is

bench eval adopt is the benchmark-adoption router. It routes an external benchmark into benchmarks/<name>/ — scaffold, codex-driven conversion, and a parity gate — so the result is a first-class BenchFlow benchmark. It sits upstream of evaluation: the router adopts, while bench eval create runs the resulting tasks. Once bench eval adopt verify <name> reports parity-confirmed, you point bench eval create at the converted tasks and run them like any other benchmark. (These commands were bench agent create|run|verify before 0.6; the old names still work as deprecated aliases through 0.6 and are removed in 0.7.) Three subcommands form the adopt → verify loop:
The reference for what a finished adoption looks like is benchmarks/programbench/; the conversion contract is benchmarks/CONVERT.md. The router embeds both into the conversion workflow for you.

bench eval adopt init <name>

init writes a deterministic scaffold under benchmarks/<name>/, matching the reference layout and the CONVERT.md contract. Use --benchmarks-dir to target a directory other than the repo’s benchmarks/:
That produces this tree:
What each file is for:
  • benchflow.py — the converter. Its documented convert() / convert_all() entry points are NotImplementedError stubs that point at CONVERT.md step 2; you fill them in to map each source instance to a Harbor-format task directory (task.toml, instruction.md, environment/Dockerfile, tests/test.sh).
  • parity_test.py — the parity harness, with --mode full | eval-parity | side-by-side (CONVERT.md steps 3–5). Side-by-side parity records the per-criterion original_verdict / adapted_verdict pairs that verify scores.
  • parity_experiment.json — the recorded parity results verify reads. The scaffold writes a status: "template" placeholder with empty conversion_parity.tasks and reward_distribution_parity.samples; you populate it from a real parity run.
  • benchmark.yaml — the standard descriptor (name, conversion method, verification method, parity tallies). Fields start as TODO/0.
main.py, run_webarena_lite.py, and webarena-lite.yaml are the converter CLI delegator, the convert-then-evaluate runner, and the BenchFlow job config respectively.

Fail-closed behavior

init refuses to overwrite an existing benchmark — re-running it is an error, not a silent clobber:
Names must be lowercase slugs (leading letter, single internal hyphens). The slug is also the security floor — it keeps init/verify from being steered outside benchmarks/. An uppercase or underscored name is rejected:
Both fail-closed cases exit non-zero.

bench eval adopt convert <source> [--name]

convert drives the conversion. It assembles an adoption prompt — the source, the target benchmarks/<name>/ path, the adoption skills (CONVERT.md, the programbench worked example, the parity harness), and the full embedded CONVERT.md guide — then launches the host codex CLI to do the conversion toward a pull request. If you omit --name, the slug is derived from the source basename (so .../webarena becomes webarena). Use --dry-run to print the exact command the router would launch without running it:
The full prompt embeds CONVERT.md verbatim (elided above). The codex exec argv is constructed deterministically: it runs in the repo root (--cd <repo>), with --skip-git-repo-check and --sandbox workspace-write. Pass --model to set the codex driver model and --codex-bin to point at a different codex binary. A live run (drop --dry-run) requires codex credentials and fails closed without them — set OPENAI_API_KEY (or CODEX_API_KEY), or run codex login to create ~/.codex/auth.json. Without credentials convert errors before assembling any context:
The codex run is the manual-validation step — it iterates on the converter and parity tests until bench eval adopt verify confirms parity.

bench eval adopt verify <name>

verify is the gate that closes the loop. It reads the adopted benchmark’s parity_experiment.json and emits a confidence verdict. The gate is parity only: a faithful conversion must reproduce the original’s behavior on identical inputs — including any reward-hackability the original has. It never “improves” or sanitizes the source. It scores two layers:
  • Conversion parity (deterministic floor) — every compared criterion’s converted verdict must match the original’s verdict on identical inputs.
  • Reward-distribution parity (statistical layer) — every legacy-vs-converted reward delta must sit within --tolerance (default 0.02).
A layer with no recorded data does not block the verdict. The three verdicts: A freshly scaffolded benchmark has no recorded parity, so it is insufficient-evidence and exits non-zero:

A parity-confirmed run

Populate parity_experiment.json from a parity run. verify reads per-criterion verdicts under conversion_parity.tasks and reward samples under reward_distribution_parity.samples:
With every criterion agreeing and every reward delta at zero, the verdict is parity-confirmed and verify exits zero:

A parity-divergent run

Flip one criterion so the converted verdict no longer matches the original (here C-002’s adapted_verdict goes from fail to pass). The deterministic floor trips, the verdict becomes parity-divergent, and verify prints a draft GitHub issue body for the support path:
The draft is never filed automatically — it is printed for a human to review and open if they need support. Pass --issue-out PATH to write it to a file instead of stdout:

The --roundtrip-task structural hook

By default verify scores the recorded parity_experiment.json at the benchmark level. Pass --roundtrip-task <task-dir> to also run the structural round-trip conformance check on one concrete task tree (it reuses the existing Harbor round-trip parity utility). It is opt-in because that harness needs a concrete task directory, which the benchmark-level verdict does not require. verify exits non-zero for parity-divergent and insufficient-evidence, and errors if the benchmark was never adopted:

From adoption to evaluation

Once verify reports parity-confirmed, the benchmark is a normal BenchFlow benchmark: run its tasks with bench eval create (see Running benchmarks), using the job config the scaffold generated. The router’s job ends at parity-confirmed; evaluation takes it from there.