improve-openui-harnesses

# Improve OpenUI harnesses Preserve one shared research-to-results system. Improve the existing owner instead of adding a parallel trainer, evaluator, artifact tree, or policy. ## Workflow 1. Read `AGENTS.md`, `docs/repository-organization.md`, and the design document named for the harness. 2. Identify the harness family in [references/harnesses.md](references/harnesses.md) and read that entire section before editing. 3. Trace its public script to the library owner, downstream artifact consumers, tests, and ship/promotion gates. 4. Change the shared owner. Keep schemas strict, paths canonical, and untrusted model/research output behind typed compilation and validation. If the file is watched by a component in `src/slm_training/resources/versions.json` (metrics, gates, eval/train harnesses, matrices, test-data builder), bump that component's version — or append a same-version `no-bump: <reason>` history entry for behavior-neutral edits — in the same change (`docs/design/version-stamp-contract.md`). 5. Add the smallest regression test that proves the new invariant. For a train, eval, benchmark, profile, telemetry, matrix, or reproduction run, also use `documenting-experiment-results`; for readiness claims use `honest-ship-eval`. 6. Run the family checks from the reference, `python -m scripts.repo_policy`, `python -m scripts.verify_version_stamps --check`, `.githooks/check-changed`, and `git diff --check`. ## Shared contracts - Keep raw campaign evidence in `outputs/autoresearch/<campaign>/`, ordinary run evidence in `outputs/runs/<run-id>/`, versioned data in `outputs/data/{train,eval}/`, and durable measured results in `docs/design/`. - Reuse `scripts/train_model.py`, `scripts.evaluate_model.py`, AgentV publication, lineage records, and the existing promotion gates. Never build shadow paths. - Preserve train/eval isolation, immutable data snapshots, honest slot contracts, checkpoint/model-card requirements, and fail-closed RL readiness. - Treat fixture/smoke evidence as wiring only. Never weaken gates to promote it. - Feed persisted outcomes and diagnoses back through evidence or typed feedback. A continuous controller may route a reproduced `HarnessSignalV1` here, but the repair must touch the canonical owner and replay the identical frozen arm. - A harness may not rewrite its own judge, frozen cases, or thresholds in the campaign it is trying to pass. Judge changes require a separate preregistered meta-campaign with unchanged held-out controls and may never weaken a gate. - Add a new harness family only when no listed owner fits, then update the reference, repository guide, policy, docs, and tests in the same change. ## Improvement evidence An improvement is incomplete until the relevant invariant has a focused test and, when execution occurred, the canonical JSON plus markdown record states recipe, suite size, result, and honest pass/fail. A self-improvement claim additionally needs frozen evaluation cases, held-out results, and the automated frozen meta-gate. Passing evidence promotes locally; external delivery remains separately authorized. ## Parameter efficiency (harness edits may not make size free) - Parameter count is a **cost**, not a field to log. A harness that records `trainable_params` and never charges it is the bug this rule exists for — route size through `scaling_fit.observation_cost` / `efficiency_gain`. - New capacity knobs are registered in `levers.CAPACITY_SCALING_LEVERS` with their baseline value and axis, the way weakening levers are registered. - Selection and promotion prefer the **smallest sufficient** model (`promotion_engine.select_smallest_sufficient`); never rank by quality alone across arms of differing size. - Do not duplicate a cost accessor. One switch, one place — a parallel copy is how `params` came to be charged by nobody. ## Decode invariants (harness edits may not weaken them) `AGENTS.md` § Non-negotiable architecture invariants is goal law; canonical expansion: [decode-invariants.md](../../../docs/design/decode-invariants.md). For harness changes specifically: - Never remove or bypass the deterministic singleton bypass (I2) or constrained legality (I6) from any decode path. A new decode path merges only with a `forwards_count == 0` bypass test. - Ranking, speculation technique, and batching are levers; legality is not. A change that can widen the legal set is not a lever, it is a regression. - New weakening levers must be registered in `levers.CONSTRAINT_WEAKENING_LEVERS` with their fail-closed value. - A rejected experiment closes an *approach*, never a *goal* (I14). When a harness change abandons an approach to an open invariant, file the successor approach in the same measured-results doc.