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evaluation-framework

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Table of Contents

Evaluation Framework

Overview

A generic framework for weighted scoring and threshold-based decision making. Provides reusable patterns for evaluating any artifact against configurable criteria with consistent scoring methodology.

This framework abstracts the common pattern of: define criteria → assign weights → score against criteria → apply thresholds → make decisions.

When To Use

  • Implementing quality gates or evaluation rubrics
  • Building scoring systems for artifacts, proposals, or submissions
  • Need consistent evaluation methodology across different domains
  • Want threshold-based automated decision making
  • Creating assessment tools with weighted criteria

When NOT To Use

  • Simple pass/fail without scoring needs

Core Pattern

1. Define Criteria

criteria:
  - name: criterion_name
    weight: 0.30          # 30% of total score
    description: What this measures
    scoring_guide:
      90-100: Exceptional
      70-89: Strong
      50-69: Acceptable
      30-49: Weak
      0-29: Poor

Verification: Run the command with --help flag to verify availability.

2. Score Each Criterion

scores = {
    "criterion_1": 85,  # Out of 100
    "criterion_2": 92,
    "criterion_3": 78,
}

Verification: Run the command with --help flag to verify availability.

3. Calculate Weighted Total

total = sum(score * weights[criterion] for criterion, score in scores.items())
# Example: (85 × 0.30) + (92 × 0.40) + (78 × 0.30) = 85.5

Verification: Run the command with --help flag to verify availability.

4. Apply Decision Thresholds

thresholds:
  80-100: Accept with priority
  60-79: Accept with conditions
  40-59: Review required
  20-39: Reject with feedback
  0-19: Reject

Verification: Run the command with --help flag to verify availability.

Quick Start

Define Your Evaluation

  1. Identify criteria: What aspects matter for your domain?
  2. Assign weights: Which criteria are most important? (sum to 1.0)
  3. Create scoring guides: What does each score range mean?
  4. Set thresholds: What total scores trigger which decisions?

Example: Code Review Evaluation

criteria:
  correctness: {weight: 0.40, description: Does code work as intended?}
  maintainability: {weight: 0.25, description: Is it readable?}
  performance: {weight: 0.20, description: Meets performance needs?}
  testing: {weight: 0.15, description: Tests detailed?}

thresholds:
  85-100: Approve immediately
  70-84: Approve with minor feedback
  50-69: Request changes
  0-49: Reject, major issues

Verification: Run pytest -v to verify tests pass.

Evaluation Workflow

**Verification:** Run the command with `--help` flag to verify availability.
1. Review artifact against each criterion
2. Assign 0-100 score for each criterion
3. Calculate: total = Σ(score × weight)
4. Compare total to thresholds
5. Take action based on threshold range

Verification: Run the command with --help flag to verify availability.

Common Use Cases

Quality Gates: Code review, PR approval, release readiness Content Evaluation: Document quality, knowledge intake, skill assessment Resource Allocation: Backlog prioritization, investment decisions, triage

Integration Pattern

# In your skill's frontmatter
dependencies: [leyline:evaluation-framework]

Verification: Run the command with --help flag to verify availability.

Then customize the framework for your domain:

  • Define domain-specific criteria
  • Set appropriate weights for your context
  • Establish meaningful thresholds
  • Document what each score range means

Detailed Resources

  • Scoring Patterns: See modules/scoring-patterns.md for detailed methodology
  • Decision Thresholds: See modules/decision-thresholds.md for threshold design

Exit Criteria

  • Criteria defined with clear descriptions
  • Weights assigned and sum to 1.0
  • Scoring guides documented for each criterion
  • Thresholds mapped to specific actions
  • Evaluation process documented and reproducible

Troubleshooting

Common Issues

Command not found Ensure all dependencies are installed and in PATH

Permission errors Check file permissions and run with appropriate privileges

Unexpected behavior Enable verbose logging with --verbose flag

Source

git clone https://github.com/athola/claude-night-market/blob/master/plugins/leyline/skills/evaluation-framework/SKILL.mdView on GitHub

Overview

Evaluation Framework provides a generic pattern for scoring artifacts against configurable criteria with weighted scores and threshold-based decisions. It enables consistent evaluation across domains by defining criteria, weights, scoring guides, and automated outcomes. Use it to build quality gates, rubrics, and decision frameworks.

How This Skill Works

Define criteria with weights, score each criterion, calculate a weighted total, and apply predefined thresholds to determine outcomes. The framework supports a clear pattern (define criteria → assign weights → score → compute total → apply thresholds) with practical examples like code review evaluations and YAML-based criteria definitions.

When to Use It

  • Implementing quality gates or evaluation rubrics
  • Building scoring systems for artifacts, proposals, or submissions
  • Need consistent evaluation methodology across different domains
  • Want threshold-based automated decision making
  • Creating assessment tools with weighted criteria

Quick Start

  1. Step 1: Define criteria and assign weights (ensure they sum to 1.0)
  2. Step 2: Create scoring guides that map score ranges to qualitative labels
  3. Step 3: Set thresholds and run the evaluation to generate a decision

Best Practices

  • Define clear criteria and assign weights that sum to 1.0
  • Provide explicit scoring guides for each criterion with score ranges
  • Align thresholds with the impact of decisions and edge cases
  • Validate the framework with sample evaluations and revisions over time
  • Version criteria definitions and reuse templates across projects

Example Use Cases

  • Code Review Evaluation using weighted criteria (correctness, maintainability, performance, testing) with explicit weights
  • Artifact evaluation for proposals or submissions against a rubric
  • Quality gates in CI pipelines that auto-approve or flag items based on scores
  • Rubric design for research or feature proposals
  • Decision frameworks for gating feature flags or deployments

Frequently Asked Questions

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