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Agentflow v0.6.0
Agentflow v0.6.0 — Lean Code Factory acceptance integrity
Changes
- Lean orchestration contract: route the smallest relevant specialist set; use DAG delegation only when the host genuinely supports workers and coordination provides value. The host, not Agentflow, remains the AI executor.
- Issue-based execution integrity: execution phases with fail-closed
ACCEPTEDchecks; a shared authoritativeResume pointerparser that rejects duplicated fields and authoritative sections; valid repository identity in the baseline. - GitHub evidence gate:
scripts/acceptance-gate.mjsrejects mismatched repository, run IDs, commit SHA, unrelated CI, wrong branches, failed jobs, and unverified requirements. Only completedCIruns triggered by apushtomasterwith a successfulverifyjob qualify. - Manual read-only GitHub workflow:
Agentflow Issue Acceptancechecks the existing Issue and CI through GitHub API; it rejects changed master/Issue state mid-check and never edits Issues, merges code, or deploys. - Regression coverage and guidance: tests for duplicate/shadowed fields, invalid Issue identities, stale CI, forged runs, and host-orchestration boundaries; documentation distinguishes opt-in evidence checks from required branch protection.
Compatibility and remaining acceptance
The original one router + ten specialist skills and skills-only distribution remain. There is no Agentflow backend, agent worker pool, scheduler, external AI model executor, npm package publish, or new API-key requirement.
GitHub Release includes the agentflow-chatgpt-v0.6.0.zip skills-only candidate. Publishing the ZIP does not update a currently installed ChatGPT plugin, establish public Plugin Directory listing, or prove cross-conversation E2E; those tests remain open in Issue #34. The manual acceptance workflow is opt-in, and repository administrators must separately configure branch-protection/required-check policy.