| name | eval |
| description | Formal evaluation framework implementing eval-driven development (EDD). Define evals before coding, run continuously, track pass@k metrics. |
Eval-Driven Development
A formal evaluation framework implementing eval-driven development (EDD) principles. Evals are the "unit tests of AI development."
Philosophy
- Define expected behavior BEFORE implementation
- Run evals continuously during development
- Track regressions with each change
- Use pass@k metrics for reliability measurement
Usage
/eval define <feature-name> # Create eval definition
/eval check <feature-name> # Run and check evals
/eval report <feature-name> # Generate full report
/eval list # Show all evals
Eval Types
Capability Evals
Test if a new capability works:
[CAPABILITY EVAL: feature-name]
Task: Description of what should be accomplished
Success Criteria:
- [ ] Criterion 1
- [ ] Criterion 2
Expected Output: Description of expected result
Regression Evals
Ensure changes don't break existing functionality:
[REGRESSION EVAL: feature-name]
Baseline: SHA or checkpoint name
Tests:
- existing-test-1: PASS/FAIL
- existing-test-2: PASS/FAIL
Result: X/Y passed
Grader Types
Code-Based Grader (Deterministic)
grep -q "export function handleAuth" src/auth.ts && echo "PASS" || echo "FAIL"
npm test -- --testPathPattern="auth" && echo "PASS" || echo "FAIL"
Model-Based Grader (Open-ended)
[MODEL GRADER PROMPT]
Evaluate the following code change:
1. Does it solve the stated problem?
2. Is it well-structured?
3. Are edge cases handled?
Score: 1-5
Human Grader
[HUMAN REVIEW REQUIRED]
Change: Description
Risk Level: LOW/MEDIUM/HIGH
Metrics
pass@k — "At least one success in k attempts"
- pass@1: First attempt success rate
- pass@3: Success within 3 attempts
- Target: pass@3 > 90%
pass^k — "All k trials succeed"
- pass^3: 3 consecutive successes
- Use for critical paths
Eval Workflow
1. Define (Before Coding)
## EVAL DEFINITION: feature-xyz
### Capability Evals
1. Can create new user account
2. Can validate email format
### Regression Evals
1. Existing login still works
2. Session management unchanged
### Success Metrics
- pass@3 > 90% for capability evals
- pass^3 = 100% for regression evals
2. Implement
Write code to pass the defined evals.
3. Evaluate
Run each eval, record PASS/FAIL.
4. Report
EVAL REPORT: feature-xyz
========================
Capability: 3/3 passed (pass@3: 100%)
Regression: 3/3 passed (pass^3: 100%)
Status: SHIP IT
Eval Storage
.codex/evals/
feature-xyz.md # Eval definition
feature-xyz.log # Eval run history
baseline.json # Regression baselines
Best Practices
- Define evals BEFORE coding
- Run evals frequently
- Track pass@k over time
- Use code graders when possible (deterministic > probabilistic)
- Human review for security
- Keep evals fast
- Version evals with code