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hao-ai-lab-FastVideo/.agents/workflows/evaluation-development.md

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description
description
How to develop, validate, and register a new evaluation metric

Evaluation Development SOP

Standard procedure for adding new video quality evaluation metrics to the FastVideo agent toolkit.

When to Use

  • You need a metric that doesn't exist in .agents/memory/evaluation-registry/README.md.
  • An existing metric needs significant changes to its methodology.
  • You're exploring a new evaluation approach.

Steps

1. Research

  • Search .agents/memory/related-work/ for existing evaluation approaches.
  • Check the evaluation_registry.md for current metrics and their limitations.
  • Review literature: FVD, CLIP-Score, human preference, etc.

2. Prototype

  • Write a standalone script in .agents/exploration/<metric-name>.md.
  • Keep it simple: one script, minimal dependencies.
  • Test on a few known-good and known-bad video samples.

3. Validate

  • Known-good test: Metric should score high on reference-quality videos.
  • Known-bad test: Metric should score low on degraded/unrelated videos.
  • Sensitivity test: Small quality differences should produce meaningful score differences.
  • Document thresholds and their justification.

4. Register

Update .agents/memory/evaluation-registry/README.md:

  • Add the metric with status Active.
  • Document location, thresholds, and trust level.

5. Integrate

Update .agents/skills/evaluate-video-quality.md:

  • Add the new metric as a section.
  • Include code examples and interpretation guide.

6. Document

  • Move the exploration log content into the skill.
  • Clean up the exploration file or mark it as promoted.
  • If anything went wrong during development, create a lesson.