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Daily Library Review

The data-driven quality loop that promotes winners and retires underperformers.

The Daily Library Review will be the automated quality assurance process that keeps your Skill Library healthy. Every day, it will analyze Output Ledger data to identify which skills are working and which need attention.

How It Works

  1. Aggregate — Collect all output data from the last 24 hours across every runtime
  2. Score — Calculate acceptance rates, rework ratios, and quality trends per skill
  3. Flag — Surface skills with declining quality or high rework rates
  4. Recommend — Suggest promotions (org-wide rollout) or retirements (skill removal)
  5. Report — Generate a daily summary for skill owners and governance leads

Quality Signals

SignalMeaningAction
High acceptance (>90%)Skill is producing quality outputConsider promotion
Rising rework (>20%)Skill output needs frequent editingFlag for revision
Low adoption (under 5 runs/week)Skill may be irrelevant or hard to findReview discoverability

Self-Improving System

The Daily Review will create a feedback loop that manual processes can't match:

  • Skills that produce consistently high-quality output get promoted to org-wide availability
  • Skills that produce rework get flagged for their authors to revise
  • Skills that consistently underperform get retired automatically