feat(skills): baseline-source ladder - greenfield and recipe-confirmed baselines - #13621
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…d baselines The interview may now produce the baseline when the user has none, with the user's explicit confirmation as the invariant at every rung: 1. user provides a DGD (origin: user) 2. exact/close catalog recipe proposed with an explicit adaptation diff (origin: recipe-confirmed) 3. no close recipe: new author-baseline-dgd skill drafts one from the interview facts and the model-sizing/knob-tuning guides, presented with a per-decision evidence table (origin: agent-authored) Selection and authoring happen ONLY at interview time; the loop still never selects. Provenance recorded as deployment.origin/origin_source; inputs/baseline-evidence.md carries the proposal, evidence table, and confirmation for rungs 2-3. Non-user origins calibrate downstream: iteration 0 is pure characterization, and the generator/challenger treat the baseline itself as a hypothesis (topology families start untested). The incompatible-baseline graceful end now offers the ladder for the follow-on engagement. Gate: two adversarial verification rounds (9 findings first round, 1 second round - all fixed); 26 skills validate. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
…tions Found in the greenfield validation room: a headless -p agent parked the engagement on a background-job notification that can never arrive in a single-shot harness. The long-running-runs guidance now distinguishes harness types explicitly. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Review feedback on #13557 (landed here to avoid dismissing its fresh approvals): SKILL.md files self-discover, but the orchestration guide with the sequencing and stopping rules does not - the dispatch section now requires the top-level agent to read it first. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
…ncy-grid The rule said 'at most 4x the concurrency' while its example said c=4 means at most 4 requests (1x). An agent following the example produces 4-request measurements that cannot support the noise-floor rules. Found by automated review on #13557; landed here to preserve that PR's approvals. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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What
Greenfield engagements, properly designed (the fast-follow cut from #13557): the interview may now produce the baseline when the user has none, with the user's explicit confirmation as the invariant at every rung:
origin: user) - unchanged.origin: recipe-confirmed).author-baseline-dgdskill drafts one from the interview facts and the model-sizing/knob-tuning guides, presented with a per-decision evidence table (origin: agent-authored).Selection and authoring happen ONLY at interview time; the loop still never selects. Provenance is recorded (
deployment.origin/origin_source;inputs/baseline-evidence.mdcarries the proposal, evidence, and confirmation). Non-user origins calibrate downstream: iteration 0 is pure characterization, and the generator/challenger treat the baseline itself as a hypothesis.Validation
Sequencing
Base is
optimization-pack-v2; after #13557 merges this retargets to main.Reviewer starting points
.agents/skills/author-baseline-dgd/SKILL.md(new)agents/user-interviewer/AGENTS.md(the ladder)agent-docs/rules/execution/user-workload.md(origin schema)🤖 Generated with Claude Code