jmagly Agent Evaluation
Run automated evaluation tests against an agent.
Research Foundation
- REF-001: BP-9 - Continuous evaluation of agent performance
- REF-002: KAMI benchmark methodology for failure archetype detection
Usage
/eval-agent security-architect
/eval-agent architecture-designer --category archetype
/eval-agent test-engineer --scenario grounding-test --verbose
Arguments
| Argument | Required | Description |
|---|---|---|
| agent-name | Yes | Agent to evaluate |
Options
| Option | Default | Description |
|---|---|---|
| --category | all | Test category: archetype, performance, quality |
| --scenario | all | Specific scenario to run |
| --verbose | false | Show detailed test output |
| --output | stdout | Output file for results |
| --strict | false | Fail on any test failure |
Test Categories
archetype
Tests for Roig (2025) failure archetypes:
grounding-test- Archetype 1: Premature actionsubstitution-test- Archetype 2: Over-helpfulnessdistractor-test- Archetype 3: Context pollutionrecovery-test- Archetype 4: Fragile execution
performance
latency-test- Response time benchmarkstoken-test- Token efficiencyparallel-test- Concurrent execution correctness
quality
output-format- Output structure validationtool-usage- Appropriate tool selectionscope-adherence- Stays within defined scope
Process
- Load Agent: Read agent definition
- Select Scenarios: Based on --category or --scenario
- Setup Environment: Create test workspace
- Execute Tests: Run agent against each scenario
- Validate Results: Check assertions
- Generate Report: Output results
Output Format
{
"agent": "security-architect",
"timestamp": "2025-01-15T10:30:00Z",
"tests": {
"grounding-test": {
"passed": true,
"score": 1.0,
"details": "Read tool called before Edit",
"duration_ms": 5000
},
"distractor-test": {
"passed": false,
"score": 0.6,
"details": "Used staging data in output",
"evidence": ["Found 'staging' in response"],
"duration_ms": 3000
}
},
"summary": {
"passed": 3,
"failed": 1,
"total": 4,
"score": 0.85
}
}
Examples
# Full evaluation
/eval-agent architecture-designer
# Archetype tests only
/eval-agent architecture-designer --category archetype
# Single scenario with verbose output
/eval-agent test-engineer --scenario grounding-test --verbose
# Save results
/eval-agent security-architect --output .aiwg/reports/security-eval.json
# Strict mode (fails on any test failure)
/eval-agent devops-engineer --strict
Success Criteria
| Metric | Target |
|---|---|
| Grounding (A1) | >90% |
| Substitution (A2) | >85% |
| Distractor (A3) | >80% |
| Recovery (A4) | ≥80% |
| Overall | ≥85% |
Related Commands
/eval-workflow- Test multi-agent workflows/eval-report- Generate quality reportaiwg lint agents- Static validation
Evaluate agent: $ARGUMENTS
References
- @$AIWG_ROOT/agentic/code/addons/aiwg-evals/README.md — aiwg-evals addon overview
- @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/god-session.md — Single-responsibility rules that agents are evaluated against
- @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/vague-discretion.md — Concrete success criteria and threshold definitions
- @$AIWG_ROOT/agentic/code/frameworks/sdlc-complete/README.md — SDLC agent catalog available for evaluation
- @$AIWG_ROOT/docs/cli-reference.md — CLI reference for aiwg lint agents