--- name: paro-evidence description: "Design or audit formal Paro performance claims: release acceptance, cross-engine parity, model calibration certification or non-inferiority. Not for routine exploration; use paro-benchmark there." --- # Paro formal evidence Daily iteration uses [paro-benchmark](../paro-benchmark/SKILL.md). Use this workflow only for a requested formal claim or its audit. Review-only work does not authorize new runs. Never bless results or evolve a policy here. ## Register, collect, decide 1. Inspect the selected checkout and existing evidence. Before confirmatory sampling, version a short registration: hypothesis/intervention, arms, independent sampling unit, sample size/power, numeric thresholds, exclusions, uncertainty, coverage/held-out rules, resources and finite storage budget. Existing pilots cannot be retrospectively preregistered. 2. Pin source/dirty content, binary/build, harness, SQL/schema/data/metadata, protocol, cache regime, DOP/memory and actual verification/observers. Follow [declared competitor baseline](../../../benchmark/CORPORA.md#declared-competitor-baseline): requirements constrain the version; the registration also identifies actual native binaries/extensions/settings. Upgrades create a new comparison. 3. Use maintained collectors with balanced/interleaved blocks. Treat the fresh process/block as the independent unit when appropriate, not each repeated warm timing. Normal measurements and diagnostic captures remain separate. 4. Validate complete types, multiplicities and required ordering outside timing. Keep every failure, retry, valid slow sample and exclusion. Explicitly bounded independent numerical certificates are not strict equality. 5. Evaluate the registered rule, including uncertainty/tails/coverage. A small median alone is not certification. Report missing evidence or confounding as Uncovered/Incomparable/NotCertified, not zero or an invented receipt. ## Comparison validity - Do not infer causal speedups from unrelated report ratios or sums/differences of cohort medians. A decomposition needs direct same-lifecycle observations. - Match inputs, admitted plan/resources, node/port/phase and units. Equal plan fingerprints locate artifacts; they are not semantic equivalence proofs. A diagnostic mismatch blocks joint attribution, not preservation of valid time. - Model comparisons must share an applicable objective/fact/resource context. A partial order has incomparable candidates: rank correlation is descriptive, not a pruning proof. Use independent small-region enumeration, measured dominance violations and selection regret for the decisions actually made. - Changing a threshold/exclusion after seeing outcomes requires a disclosed amendment and fresh confirmation where it changes the decision. ## Bounded local evidence, small durable decisions Keep raw runs in ignored `benchmark/runs//` or a declared external root, not in Git. Share campaign identities, retain samples/receipts per query/arm cell and reference each bounded compile capture once. Use the actual typed RunOutput/validator limits; don't duplicate a capacity formula in prose. Register a finite total budget and stop collection when exhausted; don't discard slow samples or gzip an oversized event stream to pass a limit. Preserve the complete raw run through review. If long-term reproducibility needs retention, explicitly name an approved artifact location, checksum and retention owner; without retained raw data, a historical decision is not a currently re-auditable certification. Git normally gets at most a page of conclusion/registration with identities, uncertainty, commands and limitations. Correctness fixtures belong in maintained tests/corpora, not historical reports. Stop confirmatory collection on result errors, identity drift, uncontrolled interference or missing required evidence. Report partial results honestly. Neither this workflow nor a successful check authorizes baseline changes, history rewriting, automatic deletion, or publication.