skill-hypothesis-discovery

To prioritize testable improvement hypotheses, analyze evidence from benchmarks and validation gaps to generate a backlog. This process selects high-impact, low-risk items by detailing observed signals, mechanisms, and expected effects without applying any file edits.

No-mutation planning is the process of dictating next steps strictly from evidence without applying patches or edits. It ensures safe governance by generating a backlog of testable hypotheses detailing validation methods and rollback notes before any code changes occur.

You can create a backlog from harness findings by extracting observed signals and validation gaps to formulate testable hypotheses. This structures your evidence into prioritized items with expected effects, validation methods, and risk notes to guide safe improvements.

Yes, you can use hypothesis discovery to plan improvements without editing files because it enforces a no-mutation governance model. It outputs a structured backlog of testable hypotheses with risk and rollback notes, ensuring evidence dictates planning before any mutation.

The best way to document validation methods and rollback risks is by structuring them into a hypothesis backlog. This approach captures observed signals, expected effects, and specific validation methods, ensuring every evidence-backed item includes comprehensive risk notes.