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效率与协作 · SKILL.md

evaluation-and-metrics

evaluation-and-metrics

【效率与协作】Evaluate DeTikZify outputs with metric wrappers, score generated TikZ programs, and reason about the repository's evaluation pipeline.

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技能说明

GitHub

name: evaluation-and-metrics description: "Evaluate DeTikZify outputs with metric wrappers, score generated TikZ programs, and reason about the repository's evaluation pipeline." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Evaluation and Metrics

Use this sub-skill when the task is about examples/eval.py, metric wrappers, score computation, comparison against references, or the evaluation side of compiled TikZ generation.

Route away from this sub-skill when the task is mostly about producing one new program, launching the web UI, or changing training loops.

Fast Path

  1. Confirm the package and compile helpers are available:
    python scripts/api_smoke.py
    python scripts/tikz_smoke.py
    
  2. Read the metric reference before trying a scoring run:
    references/metrics.md
    
  3. Read the workflow reference if you need the model-input and caching behavior:
    references/workflows.md
    

What This Sub-Skill Owns

  • the detikzify.evaluate metric wrappers
  • score aggregation over generated and reference TikZ
  • ImageSim and the perceptual scoring path
  • ClipScore, CrystalBLEU, DreamSim, KernelInceptionDistance, and TexEditDistance
  • redacted compile / rasterize metrics and token-efficiency style summaries
  • the repo's evaluation pipeline and its compile-backed checks

Common Decisions

  • Use ImageSim / model-based scoring when you want perceptual similarity.
  • Use the faster compiler-diagnostics path when you only need a cheap evaluation pass.
  • Remember that some metrics are lazily imported and need optional dependencies.
  • Keep the compile/rasterize path in mind: evaluation is not just string comparison.
  • If the task asks about redacted outputs, inspect the compileable document and the redaction step separately.

Bundled References

Guardrails

  • A metric import succeeding does not prove the model or render path works.
  • Do not ignore compile failures when the score depends on compiled TikZ.
  • Do not assume optional metric dependencies are present in a minimal install.
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