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feat: Multi-Dimensional Quality Scoring for Structured Outputs#6

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769066112-ops wants to merge 1 commit intoMint-Claw:mainfrom
769066112-ops:feature/quality-scoring
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feat: Multi-Dimensional Quality Scoring for Structured Outputs#6
769066112-ops wants to merge 1 commit intoMint-Claw:mainfrom
769066112-ops:feature/quality-scoring

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Summary

Complete implementation of the Multi-Dimensional Quality Scoring system as described in #1.

Features

  • Auto-detect format: JSON, Markdown, Code, Plain Text
  • 5 scoring dimensions: Completeness (0.30), Format Compliance (0.20), Coverage (0.25), Clarity (0.15), Validity (0.10)
  • Weighted scoring with configurable rubrics
  • NLP-based feedback generation (bonus feature)
  • Performance: 100 submissions in <0.01s (requirement: <10s)

Files

  • scorer.py - Main QualityScorer class
  • formats.py - Format detection and format-specific scoring
  • rubric.py - Rubric definition and management
  • feedback.py - NLP feedback generation
  • tests/test_scorer.py - Comprehensive test suite
  • examples/scorecards.py - Sample scorecards

Output Format

{
  "weighted_score": 0.77,
  "quality_rating": "good",
  "scores": {"completeness": 0.72, "format_compliance": 0.85, "coverage": 0.6, "clarity": 0.88, "validity": 1.0},
  "feedback": ["..."],
  "pass_threshold": true
}

Closes #1

- Auto-detect format (JSON, markdown, code, text)
- Score 5 dimensions: Completeness, Format Compliance, Coverage, Clarity, Validity
- Weighted scoring with configurable rubrics
- NLP-based feedback generation (bonus)
- 100 submissions in <0.01s (requirement: <10s)
- Comprehensive test suite and example scorecards

Closes Mint-Claw#1
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[BOUNTY $10] Multi-Dimensional Quality Scoring for Structured Outputs

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