Skill Scoring Rubric

Detailed scoring methodology for the 9-dimension quality framework. Use this to understand how scores are calculated and ensure consistent evaluation.

Scoring Overview

Total Possible Score: 140 points
Passing Grade: 105 points (75%)
A-Grade Target: 126 points (90%)
Perfect Score: 140 points (100%)

Dimension-by-Dimension Scoring

D1: Knowledge Delta (20 points)

Evaluation Method:

1. Read entire skill content
2. Identify content AI assistants already know
3. Calculate: Expert Content / Total Content
4. Apply scoring threshold

D2: Mindset + Procedures (15 points)

Component Breakdown:

• Clear Mindset/Philosophy: 5 points
• Step-by-Step Procedures: 5 points
• When/When-Not Guidance: 5 points

D3: Anti-Pattern Quality (15 points)

Component Breakdown:

• NEVER Lists with WHY: 5 points
• Concrete Examples: 5 points
• Consequences Explained: 5 points

D4: Specification Compliance (15 points)

Component Breakdown:

• Task Focus Declaration: 4 points
• Description Field Quality: 6 points
• Cross-Harness Portability: 3 points (CRITICAL for multi-agent compatibility)
• Proper Frontmatter: 1 point
• Activation Keywords: 1 point

Portability Requirements:

• No harness-specific paths (.opencode/, .claude/, .cursor/): 1 point
• No agent-specific references (Claude Code, Cursor Agent, etc.): 1 point
• Relative paths from skill directory (scripts/, references/): 1 point

Bonus Points (each independent, up to +2 total):

• Script Language Portability: +1 (Python/TS/JS scripts present in scripts/)
• References Section Format: +1 (heading exactly ## References, last H2, Markdown table with Topic | Reference | When to Use columns, Reference column cells are markdown links)
  • 0 if: wrong heading name, bullet list instead of table, bare URLs, plain-text paths, missing required columns, or section missing when references exist
  • Omission allowed without penalty when skill has nothing to reference

D5: Progressive Disclosure (15 points)

Component Breakdown:

• Navigation Hub Approach: 8 points
• References Directory: 4 points
• Category Organization: 3 points

D6: Freedom Calibration (15 points)

Calibration Types:

• Rigid (Mindset skills): Strong rules, must follow
• Balanced (Process skills): Clear steps with flexibility
• Flexible (Tool skills): Options and trade-offs

D7: Pattern Recognition (10 points)

Evaluation Method:

• Count domain keywords in description
• Check trigger scenarios present
• Verify activation clarity

D8: Practical Usability (15 points)

Component Breakdown:

• Concrete Examples: 5 points
• Runnable Code: 5 points
• Clear Structure: 5 points

D9: Eval Validation (20 points)

Component Breakdown:

• Eval Directory Structure: 4 points
• Instruction Inventory (instructions.json): 3 points
• Coverage Statistics (summary.json): 3 points
• Coverage >= 80%: 3 points
• Valid Scenarios (>=3 complete): 4 points
• Criteria Quality (sum to 100): 3 points

Enrichment: When instructions.json exists, D1 and D3 scores are enriched with instruction classification data (why_given distribution for D1, anti-pattern instruction count for D3).

Grade Assignment

Scoring Process

Step 1: Read and Understand

Read the entire skill, including all references if present.

Step 2: Score Each Dimension

Apply rubric to each of 9 dimensions independently.

Step 3: Calculate Total

Sum all 9 dimension scores for total out of 140.

Step 4: Assign Grade

Map total score to grade using grade assignment table.

Step 5: Identify Improvements

For scores below A-grade, identify specific improvements needed.

Common Score Patterns

High Knowledge Delta, Low Usability (18, 10): Expert content but lacks examples
Low Knowledge Delta, High Usability (10, 14): Tutorial-heavy, needs expert focus
Perfect Spec, Poor Content (15, 8): Great frontmatter, weak body
Balanced Scores (12-13 each): Consistent but not exceptional

See Also

• framework-dimensions.md - Dimension definitions
• framework-quality-standards.md - A-grade requirements