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"grade", "mode": "baseline", "draw": 0, "sample": 4, "model": "claude-haiku-5-5", "reported_models": [ "claude-haiku-5-5" ] }, { "phase": "generation", "case": "grade", "mode": "baseline", "draw": 1, "sample": null, "model": "claude-sonnet-5-5", "reported_models": [ "claude-sonnet-5-5" ] }, { "phase": "judge", "case": "grade", "mode": "baseline", "draw": 1, "sample": 0, "model": "claude-haiku-5-5", "reported_models": [ "claude-haiku-5-5" ] }, { "phase": "judge", "case": "grade", "mode": "baseline", "draw": 1, "sample": 1, "model": "claude-haiku-5-5", "reported_models": [ "claude-haiku-5-5" ] }, { "phase": "judge", "case": "grade", "mode": "baseline", "draw": 1, "sample": 2, "model": "claude-haiku-5-5", "reported_models": [ "claude-haiku-5-5" ] }, { "phase": "judge", "case": "grade", "mode": "baseline", "draw": 1, "sample": 3, "model": "claude-haiku-5-5", "reported_models": [ "claude-haiku-5-5" ] }, { "phase": "judge", "case": "grade", "mode": "baseline", "draw": 1, "sample": 4, "model": "claude-haiku-5-5", "reported_models": [ "claude-haiku-5-5" ] }, { "phase": "generation", "case": "grade", "mode": "baseline", "draw": 2, "sample": null, "model": "claude-sonnet-5-5", "reported_models": [ "claude-sonnet-5-5" ] }, { "phase": "judge", "case": "grade", "mode": "baseline", "draw": 2, "sample": 0, "model": "claude-haiku-5-5", "reported_models": [ "claude-haiku-5-5" ] }, { "phase": "judge", "case": "grade", "mode": "baseline", "draw": 2, "sample": 1, "model": "claude-haiku-5-5", "reported_models": [ "claude-haiku-5-5" ] }, { "phase": "judge", "case": "grade", "mode": "baseline", "draw": 2, "sample": 2, "model": "claude-haiku-5-5", "reported_models": [ "claude-haiku-5-5" ] }, { "phase": "judge", "case": "grade", "mode": "baseline", "draw": 2, "sample": 3, "model": "claude-haiku-5-5", "reported_models": [ "claude-haiku-5-5" ] }, { "phase": "judge", "case": "grade", "mode": "baseline", "draw": 2, "sample": 4, "model": "claude-haiku-5-5", "reported_models": [ "claude-haiku-5-5" ] } ] } }, "counts": { "generations_per_arm": 3 } } ], "aggregates": { "with_skill": { "case_count": 3, "pass_count": 3, "borderline_count": 0, "mean_score": 0.936111, "stddev": 0.074691 }, "baseline": { "case_count": 3, "pass_count": 2, "borderline_count": 0, "mean_score": 0.802222, "stddev": 0.229525 }, "band_rule": "per arm: the sample standard deviation (n-1) of the per-case means across the included cases; the comparison band is the quadrature sum of the two arms; null where an arm has fewer than two included cases" } }, "comparison": { "with_skill_score": 0.936111, "baseline_score": 0.802222, "delta": 0.133889, "delta_uncertainty": 0.241372 }, "verification_level": "TESTED", "receipt_hash": "65231f29050580d7e14324c7aff5bfc053844d5c11093958713393e98283c26c", "economics": { "basis": "metered-equivalent", "surface": "claude-cli", "with_skill": { "call_count": 10, "mean_input_tokens": 5194.6, "mean_output_tokens": 911.1, "mean_cost_usd_per_call": 0.0195, "median_wall_ms": 9387.5, "wall_ms_p25": 8513, "wall_ms_p75": 10565, "wall_ms_iqr": 2052 }, "baseline": { "call_count": 11, "mean_input_tokens": 2022.82, "mean_output_tokens": 892, "mean_cost_usd_per_call": 0.012966, "median_wall_ms": 9553, "wall_ms_p25": 8144, "wall_ms_p75": 13106, "wall_ms_iqr": 4962 }, "skill_incremental_cost_usd_per_call": 0.006534, "skill_incremental_cost_usd_per_1k_calls": 6.534, "output_tokens_delta": 19.1, "median_wall_ms_delta": -165.5, "judge_excluded": true, "judge_overhead": { "note": "Measurement overhead imposed by Driftproof, NOT a cost of running the skill. Excluded from every field above. Counted over every draw sent to the judge, each once: the usage its answered judge samples reported, at the frozen judge price. Retried attempts and samples that reported no usage are not in it.", "total_cost_usd": 0.085776, "case_rows_measured": 6, "judged_draws_counted": 21, "judged_draws_missing_usage": 0 }, "notes": { "absolute_cost": "Absolute per-call cost on a CLI surface includes a fixed harness preamble (observed ~25k input tokens on claude-cli, ~11k on codex) that we do not control. It is identical in the with-skill and baseline arms, so it cancels in the Δ figures — read the incremental columns, not the absolute ones.", "cache_pricing": "Cached input tokens are costed at the list input rate (an over-estimate where caching is heavy); cached_tokens is recorded per call so a reader can recompute.", "latency": "observed on subscription CLI surface, indicative" } } }