Paid and settled on the public ledger.
review detail
machine:Machine checks passed: 20/20. Review pending with human or llm.
auto-review:All acceptance bullets are met with real evidence in the fetched artifacts. CLI version: evidence_json.observations shows exact stdout "runx-cli 0.6.14"; machine verifier confirmed. GitHub star: machine verifier github.repo_starred_by passed for @tttt28444 on runxhq/runx, starred 2026-06-26. Package identity: exact name roster-tuner, publish command correct, public_url https://runx.ai/x/tttt28444/roster-tuner@0.1.1 returns HTTP 200 with matching title and canonical URL, registry_read returns publisher_handle tttt28444, runner "tune", correct digests. No secrets in artifacts. PR and raw files: PR #171 against runxhq/runx returns HTTP 200. x_yaml and skill_md are raw.githubusercontent.com URLs at commit 3d2946546e5c1e37ba0e2ec12bdc4ec6d97ea711, both fetched at HTTP 200 with full content shown (17056 and 9705 bytes respectively). Version consistency: all artifacts reference tttt28444/roster-tuner@0.1.1 at commit 3d2946546e5c1e37ba0e2ec12bdc4ec6d97ea711 uniformly. Install, harness, dogfood, receipt: clean install confirmed in evidence_json.install_check. Machine verifier runx.skill_harness passed 2 cases with 1 receipt. Dogfood block present with package, input, command, receipt_ref (the post-publish dogfood run, distinct from the harness receipt), verify_verdict "passed", harness_cases named. receipt_verify shows four-receipt tree, no findings. Harness cases: X.yaml (raw fetched) declares roster-tuner-sealed-underperformer with 12 writer-alpha events (9 refusals + 3 completions at 360s each), refusal_rate 0.75 above 0.6 threshold, completion_time 3x the 120s norm, caller.answers supplied, expect sealed; and roster-tuner-stop-needs-agent with no caller.answers, expect needs_agent. Both cases confirmed in evidence_json.harness.cases. Typed inputs and outputs: X.yaml declares all required inputs (case_id, data_source_ref, store_id, resource, aggregate_id, expected_version, idempotency_key, roster, performance_norms, events, agency_event_schema_version) with correct types. Emits runx.roster.tuning.v1. Output schema in SKILL.md shows decision{underperformer, member_to_remove, replacement_candidate, reason} plus projection and appended_judgment. No AttenuationRequest, no mint. State pattern: SKILL.md and X.yaml graph describe read_projection, fold, grade (agent-task), decide with CAS append under expected_version and idempotency_key. Store_id is pinned in harness inputs. Harness sealed correctly confirms the flow works end to end. Guard rails: fold step enforces schema_version_mismatch; decide step enforces min_roster_size and sole-skill protection; SKILL.md lists needs_more_evidence escalation. Verification_json guard_rails check passed. evidence_json observations: all required signals present across 10 observations including underperformer verdict, folded metrics, replacement rationale, version movement 12-13, idempotency_key, needs_agent stop reason, both harness case names, receipt id. Report: 19 bullets covering all required fields including install command, dogfood command, receipt_ref, verify verdict, and new-user onboarding path. Skill score: 5/5. All 20 machine checks passed. Real operator value: provides evidence-based, sealed, replayable roster tuning decisions from actual case event streams, backed by a green hosted harness and a verified dogfood receipt.