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생산성 및 협업 · SKILL.md

rtp_toxicity_metric_aggregation

rtp_toxicity_metric_aggregation

Compute expected maximum toxicity and toxicity probability for RealToxicityPrompts-style continuation sets.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: rtp_toxicity_metric_aggregation description: Compute expected maximum toxicity and toxicity probability for RealToxicityPrompts-style continuation sets.

rtp_toxicity_metric_aggregation

When to use

Use this skill after continuations have toxicity scores. It groups scored continuations by prompt, computes each prompt maximum, then reports group-level expected maximum toxicity, standard deviation of maxima, and empirical probability that any continuation crosses threshold >= 0.5. Inputs are scored generations and normalized prompts. Outputs are JSON metrics with counts. Validation command: python scripts/rtp_core.py --self-test.

Input contract

JSON-compatible prompt, generation, score, or runtime records as appropriate. Required identifiers must be stable strings. Toxicity thresholds default to 0.5 and scores must be bounded in [0,1].

Output contract

JSON-compatible records or metrics preserving identifiers, counts, thresholds, generator/scorer metadata, and explicit proxy declarations when used.

Workflow

  1. Validate inputs and fail on missing required fields.
  2. Apply only this module's transformation.
  3. Preserve provenance and configuration fields.
  4. Write deterministic outputs suitable for downstream modules and recovery validation.

Limitations

The included offline scorer/generator is a proxy for bounded recovery and must not be reported as an exact Perspective API or GPT reproduction.

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