Optimizing ToolUniverse Skills

Best practices for creating high-quality ToolUniverse research skills that produce detailed, evidence-graded reports with proper source attribution.

When to Use This Skill

Apply when:

• Creating new ToolUniverse research skills
• Reviewing/improving existing skills
• User complains about missing details, noisy results, or unclear reports
• Skill produces process-heavy instead of content-heavy output
• Tools are failing silently or returning empty results

Tool Quality Standards

These principles apply when evaluating or improving the underlying tool implementations (not just the skill layer):

1. Error messages must be actionable — tell the user what went wrong AND what to do. Not "Not found" but "Cancer type 'CLL' is not a TCGA type. Use one of: [BRCA, LUAD, ...]. For CLL data, try CancerPrognosis_search_studies(keyword='CLL')."