skill-conductor-v1

Automate skill building pipelines by chaining guidance, engineering, and compression stages end-to-end, enforcing independent quality gates that validate artifacts before passing them downstream. This orchestration eliminates manual coordination and ensures reproducible build traces.

Self-assessed quality scores hide defects because developers may inflate ratings to meet arbitrary bars, missing edge cases that only independent adversarial testing can expose. Final acceptance should use the minimum of re-audit and attacker battery results to prevent inflated assessments.

When a quality gate fails during skill pipeline orchestration, the process loops back to the owning stage for fixes and never passes failing artifacts downstream. If the loop cap is hit, it stops with a clear stopped_unmet verdict instead of faking a pass.

Yes, pipeline automation can generate machine-checkable run logs conforming to a defined JSON schema, recording every stage attempt and gate result. This provides a reproducible build trace for industrial-grade shipped artifacts.

Adversarial testing works with skill orchestration by running an independent attacker battery that evaluates real-world performance. Final acceptance uses the minimum of these attacker results and re-audit scores, ensuring self-assessed quality can never exceed actual performance.

The best way to build an industrial-grade shipped artifact is driving the skill through a full guidance, engineer, and zipper pipeline with automatic quality gate checks and honest final verdicts. This enforces strict validation and eliminates hidden defects before shipping.