evaluator-calibration
CommunityCalibrate reviewer consistency to maintain accurate evaluations over time.
Software Engineering#AI evaluation#evaluator calibration#reproducible grading#reviewer consistency#rubric-based learning
AuthorArchive228
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps maintain the consistency and accuracy of reviewer evaluations by calibrating the reviewer persona with few-shot rubric examples, preventing leniency drift over long runs.
Core Features & Use Cases
- Calibration with Examples: Uses concrete pass/fail examples to anchor the rubric and prevent leniency drift.
- Reproducible Verdicts: Ensures the same artifact evaluated by the same reviewer at different times yields the same verdict.
- Use Case: When setting up a critic/evaluator/judge agent in a multi-agent loop, or when noticing evaluator scores drifting upward without a change in output quality.
Quick Start
Run the 'evaluator-calibration' skill with the provided examples and rubric to calibrate your reviewer agent.
Dependency Matrix
Required Modules
None requiredComponents
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: evaluator-calibration Download link: https://github.com/Archive228/loopkit/archive/main.zip#evaluator-calibration Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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