/eval-agent

namespace: aiwg
name: eval-agent
platforms: [all]
description: Run evaluation tests against an agent to assess quality and archetype resistance

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 action
• `substitution-test` - Archetype 2: Over-helpfulness
• `distractor-test` - Archetype 3: Context pollution
• `recovery-test` - Archetype 4: Fragile execution

performance

• `latency-test` - Response time benchmarks
• `token-test` - Token efficiency
• `parallel-test` - Concurrent execution correctness

quality

• `output-format` - Output structure validation
• `tool-usage` - Appropriate tool selection
• `scope-adherence` - Stays within defined scope

Process

1. **Load Agent**: Read agent definition 2. **Select Scenarios**: Based on --category or --scenario 3. **Setup Environment**: Create test workspace 4. **Execute Tests**: Run agent against each scenario 5. **Validate Results**: Check assertions 6. **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 report
• `aiwg 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