How do I install the Eval Harness skill?

Run npx skillmds@latest add peopleforrester/eval-harness in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Eval Harness safe to use?

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Which AI agents work with Eval Harness?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Eval Harness free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under MIT.

Who published Eval Harness?

peopleforrester (@peopleforrester) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Eval Harness by peopleforrester — Agent Skill

Name: Eval Harness
Author: peopleforrester

File contents

Evaluation Harness

Structured framework for evaluating code quality with repeatable, evidence-based scoring.

Evaluation Dimensions

Default Rubric

Dimension	Weight	Description
Correctness	30%	Tests pass, logic correct, edge cases handled
Security	20%	OWASP compliance, input validation, secrets
Performance	15%	Efficient queries, algorithms, caching
Maintainability	15%	Readability, modularity, naming
Testing	10%	Coverage, test quality, isolation
Documentation	10%	Accuracy, completeness, examples

Scoring Scale

Score	Label	Criteria
5	Excellent	Exceeds standards, exemplary
4	Good	Meets all standards
3	Acceptable	Meets minimum, room for improvement
2	Below Standard	Missing key requirements
1	Poor	Significant issues, needs rework

Evaluation Process

1. Evidence Collection

For each dimension, gather concrete evidence:

#### Correctness Evidence
- Tests: 142 passing, 0 failing
- Edge cases: null handling verified in auth module
- Regression: no known regressions
- Score: 4/5 (missing boundary value tests for pagination)

2. Scoring

Apply scores with justification:

| Dimension | Score | Evidence |
|-----------|-------|----------|
| Correctness | 4/5 | Tests pass, missing pagination edge cases |
| Security | 3/5 | Input validation present, missing rate limiting |
| Performance | 4/5 | Queries optimized, indexes present |
| Maintainability | 5/5 | Clean architecture, clear naming |
| Testing | 3/5 | 72% coverage, below 80% target |
| Documentation | 4/5 | API docs current, missing setup guide update |

3. Weighted Score Calculation

Total = (4×0.30) + (3×0.20) + (4×0.15) + (5×0.15) + (3×0.10) + (4×0.10)
      = 1.20 + 0.60 + 0.60 + 0.75 + 0.30 + 0.40
      = 3.85 / 5.0

4. Verdict

Range	Verdict	Action
4.0-5.0	SHIP IT	Ready for production
3.0-3.9	IMPROVE	Address findings before shipping
< 3.0	REWORK	Significant issues need resolution

Custom Rubrics

Define project-specific rubrics:

rubric:
  - name: API Design
    weight: 25%
    checks:
      - RESTful conventions followed
      - Consistent error response format
      - Pagination on list endpoints
  - name: Database
    weight: 25%
    checks:
      - Migrations are reversible
      - Indexes cover common queries
      - No N+1 query patterns

Integration

Use with:

/eval command for on-demand evaluation
/verify command as part of pre-PR checks
CI pipeline as automated quality gate

---name: eval-harnessdescription: Structured evaluation framework for measuring code quality across multiple dimensions. Provides repeatable, scored assessments with evidence-based ratings.license: MIT---# Evaluation HarnessStructured framework for evaluating code quality with repeatable,evidence-based scoring.## Evaluation Dimensions### Default Rubric| Dimension | Weight | Description ||-----------|--------|-------------|| Correctness | 30% | Tests pass, logic correct, edge cases handled || Security | 20% | OWASP compliance, input validation, secrets || Performance | 15% | Efficient queries, algorithms, caching || Maintainability | 15% | Readability, modularity, naming || Testing | 10% | Coverage, test quality, isolation || Documentation | 10% | Accuracy, completeness, examples |### Scoring Scale| Score | Label | Criteria ||-------|-------|----------|| 5 | Excellent | Exceeds standards, exemplary || 4 | Good | Meets all standards || 3 | Acceptable | Meets minimum, room for improvement || 2 | Below Standard | Missing key requirements || 1 | Poor | Significant issues, needs rework |## Evaluation Process### 1. Evidence CollectionFor each dimension, gather concrete evidence:```markdown#### Correctness Evidence- Tests: 142 passing, 0 failing- Edge cases: null handling verified in auth module- Regression: no known regressions- Score: 4/5 (missing boundary value tests for pagination)```### 2. ScoringApply scores with justification:```markdown| Dimension | Score | Evidence ||-----------|-------|----------|| Correctness | 4/5 | Tests pass, missing pagination edge cases || Security | 3/5 | Input validation present, missing rate limiting || Performance | 4/5 | Queries optimized, indexes present || Maintainability | 5/5 | Clean architecture, clear naming || Testing | 3/5 | 72% coverage, below 80% target || Documentation | 4/5 | API docs current, missing setup guide update |```### 3. Weighted Score Calculation```Total = (4×0.30) + (3×0.20) + (4×0.15) + (5×0.15) + (3×0.10) + (4×0.10) = 1.20 + 0.60 + 0.60 + 0.75 + 0.30 + 0.40 = 3.85 / 5.0```### 4. Verdict| Range | Verdict | Action ||-------|---------|--------|| 4.0-5.0 | SHIP IT | Ready for production || 3.0-3.9 | IMPROVE | Address findings before shipping || < 3.0 | REWORK | Significant issues need resolution |## Custom RubricsDefine project-specific rubrics:```yamlrubric: - name: API Design weight: 25% checks: - RESTful conventions followed - Consistent error response format - Pagination on list endpoints - name: Database weight: 25% checks: - Migrations are reversible - Indexes cover common queries - No N+1 query patterns```## IntegrationUse with:- `/eval` command for on-demand evaluation- `/verify` command as part of pre-PR checks- CI pipeline as automated quality gate

Frequently asked questions

Eval Harness