claude

Continuous Learning

Signal capture, learning validation, effectiveness tracking and loop failure modes.

0 on GitHubby Quality Engineering Platform Teamv3.3.0MITupdated 3 months agogovernance
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Plugin qa-continuous-learning from marketplace qz-agent-clusters in Qualizeal/skills. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (4)

  • effectiveness-tracking

    Track correction rate, rejection rate, outcome accuracy and attributable escapes per agent, and report honestly when the correction rate is flat. Use when reviewing whether the agent ecosystem is actually improving.

  • learning-loop-failure-modes

    Symptoms and fixes for loop theatre, over-fitting to one reviewer, prompt sprawl, silent rejection and stale learnings. Use when the feedback loop looks busy but quality is not improving.

  • learning-validation

    The evidence bar before a learning is written into a shared skill — at least three similar corrections — and the record each change must carry. Use before propagating any change to shared guidance.

  • signal-capture

    Collect corrections, rejections, outcome signals and escaped defects, and classify each learning to its correct destination — skill, knowledge fabric, agent prompt or human. Use during retrospectives or after a defect escape.

Subagents (1)

  • continuous-learning

    Closes the feedback loop — captures reviewer corrections and outcome signals, feeds validated learnings back into the knowledge fabric, and tracks whether agent output quality is improving. Use during retrospectives, after defect escapes, or when reviewing agent performance.

View source on GitHub

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