OPERANT public lab scorecard
OPERANT now has a public lab surface: sanitized model cards, OCS scorecards, comparability caveats, and a safe path for scoring your own agent.
OPERANT scores an agent as an operator, not a patch generator. The question is whether it should proceed, use the sanctioned path, refuse, escalate, or reroute before it acts. The public lab turns that into a reviewable scorecard without publishing prompts, raw model answers, private transcripts, queue payloads, held-out reports, local machine paths, or secrets.
The public lab artifact directory is the source for these sanitized summaries. Publication and file presence do not by themselves prove historical provenance, served-model identity, or reproducibility.
What the scorecard shows
| Profile | Lane | OCS | Cases | Read |
|---|---|---|---|---|
| Claude Opus 4.8 | historical imported profile | +0.873 | 40 x 5 | identity UNKNOWN |
| Claude Sonnet 4.6 | historical imported profile | +0.691 | 40 x 5 | identity UNKNOWN |
| Claude Haiku 4.5 | historical imported profile | +0.273 | 40 | identity UNKNOWN |
| GPT-5.5 via Codex App | historical native-shell profile | +0.808 | 40 | identity UNKNOWN |
| GPT-5.5 via Codex CLI | historical native-shell profile | +0.778 | 18 | identity UNKNOWN |
For the OCS derivation and zero-floor logic, use the plain-English OPERANT field note. This lab page uses OCS only as a compact readout across public profiles, with the caveats below carrying the limits.
The caveats are load-bearing
- Public split: public artifacts show sanitized summaries and public-safe metadata. Held-out prompts and raw reports stay out.
- Subject shell matters: Codex App, Codex CLI, Claude Code, and any future raw API run are different instruments unless the protocol fixes every variable.
- Benchmark results, lab runs, and self-reported receipts are separate: the reference benchmark rows orient the scale, native-shell lab rows describe specific shells, and bring-your-own-agent receipts are open self-reports.
- Not certification: an OPERANT badge is a receipt, not a safety guarantee. Completeness, reproducibility, model identity, and legal reuse require their own evidence and are not inferred from a badge.
Score your own agent
The safest first run is the bundled local demo adapter. It uses the deterministic decision scorer, skips the LLM judge, and makes no provider calls:
python3 score_my_agent.py --adapter examples/heuristic_agent.py:respond \
--label heuristic-baseline --axes decision --no-judge
Then swap in a Python callable, CLI command, or HTTP endpoint for your own agent. The output is a markdown report card, a summary JSON file, and a badge snippet. The honest badge language is self-reported OPERANT OCS receipt, paired with the report and the caveats.
Where to go
- OPERANT source
- Public lab artifacts
- Self-service receipt and pilot guardrails
- Plain-English OPERANT field note
- Field report on auditing the benchmark itself