evaluation-framework

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