advise

To search prior learnings, query the knowledge registry using your goal description to retrieve credible, versioned guidance and structured reports detailing what worked, what failed, and recommended parameters.

The best way to avoid duplicate efforts is to scan the skills registry to evaluate candidate skills by category relevance and frontmatter credibility, presenting a prioritized set of historical guidance and evolution notes.

Yes, you can get decision-support context by searching the knowledge registry to assess top matches, returning a structured summary with evolution notes and recommended parameters to inform your experimental setup.

You evaluate candidate skills by scanning the skills registry to check category relevance, frontmatter credibility, and available version history, yielding a prioritized set of guidance for your specific task.

A structured report from a skills registry search includes what worked, what failed, evolution notes, and recommended parameters to fully inform your decision making before starting work.

You should not use a knowledge registry search when no prior learnings exist for your specific task, as the credibility evaluation relies on available history and frontmatter to generate a structured report.