claude

serjsmor-skills

Reusable Claude Code and Codex skills for DSPy experimentation, active learning, and continuous quality audit workflows.

5 on GitHubby Serj Smorodinskyv0.3.0MITupdated 5 months ago
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Plugin serjsmor-skills from marketplace serjsmor-skills in SerjSmor/skills. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (3)

  • active-learning

    Use when building an active learning loop for low-label predictive tasks, where a model is trained on a small labeled set, used to score an unlabeled pool, and then used to select the next batch for annotation or review.

  • continuous-quality-audit

    Use when continuously auditing model outputs to verify that they remain normal, stable, and policy-compliant over time, including sampling, drift detection, LLM-as-judge review, and storage of flagged outputs for follow-up.

  • dspy

    Use when setting up, refactoring, or iterating on a DSPy experiment workflow, especially when you need to choose an optimizer, structure an experiment folder, name iterations consistently, or log compile/eval tokens, cost, and runtime separately. This skill is for agent-assisted DSPy experimentation

View source on GitHub

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