/eval-workflow
Run evaluation tests against a multi-agent workflow to assess orchestration quality and failure archetype resistance
$ npx -y skills add jmagly/aiwg --skill eval-workflow --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/eval-workflow
Context preview
The summary Claude sees to decide when to auto-load this skill.
Run evaluation tests against a multi-agent workflow to assess orchestration quality and failure archetype resistance
SKILL.md
eval-workflow.SKILL.mdnamespace: aiwg
name: eval-workflow
platforms: [all]
description: Run evaluation tests against a multi-agent workflow to assess orchestration quality and failure archetype resistance
Workflow Evaluation
Run automated evaluation tests against a multi-agent workflow.
Research Foundation
- **REF-001**: BP-9 - Continuous evaluation of agent performance
- **REF-002**: KAMI benchmark methodology for real agentic task evaluation
Usage
/eval-workflow flow-security-review-cycle
/eval-workflow flow-inception-to-elaboration --scenario distractor-test
/eval-workflow flow-deploy-to-production --verbose --strict
Arguments
| Argument | Required | Description | |----------|----------|-------------| | workflow-name | Yes | Workflow (flow command) to evaluate |
Options
| Option | Default | Description | |--------|---------|-------------| | --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 | | --timeout | 300 | Maximum seconds per scenario |
What Gets Evaluated
Orchestration Quality
- **Agent coordination**: Parallel agents launched correctly in single message
- **Handoff fidelity**: Artifacts pass correctly between phases
- **Gate enforcement**: Phase gates checked before transition
Archetype Resistance
- `grounding-test` — Archetype 1: Premature action without reading state
- `distractor-test` — Archetype 3: Context pollution from irrelevant artifacts
- `recovery-test` — Archetype 4: Fragile execution when subagent fails
Output Validation
- Required artifacts created in correct `.aiwg/` paths
- Document structure matches templates
- Traceability links intact
Process
1. **Load Workflow**: Read flow command definition 2. **Select Scenarios**: Based on --scenario flag or all applicable 3. **Setup Workspace**: Create isolated `.aiwg/working/` test space 4. **Execute Flow**: Run workflow against each scenario 5. **Validate Outputs**: Check artifact presence, structure, and content 6. **Generate Report**: Output results with pass/fail per assertion 7. **Cleanup**: Remove test workspace
Output Format
{
"workflow": "flow-security-review-cycle",
"timestamp": "2026-04-01T10:30:00Z",
"scenarios": {
"grounding-test": {
"passed": true,
"score": 1.0,
"assertions": [
{"name": "threat-model-created", "passed": true},
{"name": "security-gate-run", "passed": true}
],
"duration_ms": 45000
},
"distractor-test": {
"passed": false,
"score": 0.7,
"assertions": [
{"name": "correct-assets-only", "passed": false, "evidence": "Distractor file referenced in output"}
],
"duration_ms": 38000
}
},
"summary": {
"passed": 4,
"failed": 1,
"total": 5,
"score": 0.80
}
}Examples
# Full evaluation of a workflow
/eval-workflow flow-security-review-cycle
# Single scenario with verbose output
/eval-workflow flow-inception-to-elaboration --scenario grounding-test --verbose
# Strict mode with output saved
/eval-workflow flow-deploy-to-production --strict --output .aiwg/reports/deploy-eval.json
Success Criteria
| Metric | Target | |--------|--------| | Artifact creation | 100% | | Grounding compliance | >90% | | Distractor resistance | >80% | | Recovery success | ≥80% | | Overall | ≥85% |
Related Commands
- `/eval-agent` - Test individual agents
- `/eval-report` - Generate aggregate quality report
- `aiwg lint agents` - Static validation
Evaluate workflow: $ARGUMENTS
References
- @$AIWG_ROOT/agentic/code/addons/aiwg-evals/README.md — aiwg-evals addon overview
- @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/subagent-scoping.md — Parallel agent coordination rules evaluated in workflows
- @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/vague-discretion.md — Concrete success thresholds and test criteria
- @$AIWG_ROOT/agentic/code/frameworks/sdlc-complete/README.md — SDLC flow commands available for workflow evaluation
- @$AIWG_ROOT/docs/cli-reference.md — CLI reference for aiwg lint and eval commands
Read more
namespace: aiwg name: eval-workflow platforms: [all] description: Run evaluation tests against a multi-agent workflow to assess orchestration quality and failure archetype resistance
Workflow Evaluation
Run automated evaluation tests against a multi-agent workflow.
Research Foundation
- **REF-001**: BP-9 - Continuous evaluation of agent performance
- **REF-002**: KAMI benchmark methodology for real agentic task evaluation
Usage
/eval-workflow flow-security-review-cycle /eval-workflow flow-inception-to-elaboration --scenario distractor-test /eval-workflow flow-deploy-to-production --verbose --strict
Arguments
| Argument | Required | Description | |----------|----------|-------------| | workflow-name | Yes | Workflow (flow command) to evaluate |
Options
| Option | Default | Description | |--------|---------|-------------| | --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 | | --timeout | 300 | Maximum seconds per scenario |
What Gets Evaluated
Orchestration Quality
- **Agent coordination**: Parallel agents launched correctly in single message
- **Handoff fidelity**: Artifacts pass correctly between phases
- **Gate enforcement**: Phase gates checked before transition
Archetype Resistance
- `grounding-test` — Archetype 1: Premature action without reading state
- `distractor-test` — Archetype 3: Context pollution from irrelevant artifacts
- `recovery-test` — Archetype 4: Fragile execution when subagent fails
Output Validation
- Required artifacts created in correct `.aiwg/` paths
- Document structure matches templates
- Traceability links intact
Process
1. **Load Workflow**: Read flow command definition 2. **Select Scenarios**: Based on --scenario flag or all applicable 3. **Setup Workspace**: Create isolated `.aiwg/working/` test space 4. **Execute Flow**: Run workflow against each scenario 5. **Validate Outputs**: Check artifact presence, structure, and content 6. **Generate Report**: Output results with pass/fail per assertion 7. **Cleanup**: Remove test workspace
Output Format
{
"workflow": "flow-security-review-cycle",
"timestamp": "2026-04-01T10:30:00Z",
"scenarios": {
"grounding-test": {
"passed": true,
"score": 1.0,
"assertions": [
{"name": "threat-model-created", "passed": true},
{"name": "security-gate-run", "passed": true}
],
"duration_ms": 45000
},
"distractor-test": {
"passed": false,
"score": 0.7,
"assertions": [
{"name": "correct-assets-only", "passed": false, "evidence": "Distractor file referenced in output"}
],
"duration_ms": 38000
}
},
"summary": {
"passed": 4,
"failed": 1,
"total": 5,
"score": 0.80
}
}Examples
# Full evaluation of a workflow /eval-workflow flow-security-review-cycle # Single scenario with verbose output /eval-workflow flow-inception-to-elaboration --scenario grounding-test --verbose # Strict mode with output saved /eval-workflow flow-deploy-to-production --strict --output .aiwg/reports/deploy-eval.json
Success Criteria
| Metric | Target | |--------|--------| | Artifact creation | 100% | | Grounding compliance | >90% | | Distractor resistance | >80% | | Recovery success | ≥80% | | Overall | ≥85% |
Related Commands
- `/eval-agent` - Test individual agents
- `/eval-report` - Generate aggregate quality report
- `aiwg lint agents` - Static validation
Evaluate workflow: $ARGUMENTS
References
- @$AIWG_ROOT/agentic/code/addons/aiwg-evals/README.md — aiwg-evals addon overview
- @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/subagent-scoping.md — Parallel agent coordination rules evaluated in workflows
- @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/vague-discretion.md — Concrete success thresholds and test criteria
- @$AIWG_ROOT/agentic/code/frameworks/sdlc-complete/README.md — SDLC flow commands available for workflow evaluation
- @$AIWG_ROOT/docs/cli-reference.md — CLI reference for aiwg lint and eval commands
Multi-agent AI framework for Claude Code, Copilot, Cursor, Warp, and 6 more platforms 200+ agents, 109+ CLI commands, 400+ deployable agent/skill/command/rule artifacts, 8 core frameworks, 32 addons, and a 40-plugin Claude Code marketplace.
Repo: jmagly/aiwg
Other skills on aiwg.
- /agent-loop-ext
Crash-resilient external agent loop with state persistence and CI/CD integration
Open skill - /agent-loop
Detect requests for iterative autonomous agent loops and route to the appropriate loop executor
Open skill - /auto-test-execution
Automatically execute tests when code-generating agents modify source files, enforcing the execute-before-return pattern
Open skill - /cross-task-learner
Enable agent loops to learn from similar past tasks and share patterns across loops
Open skill - /debug-memory
Query and manage the executable feedback debug memory
Open skill - /execute-feedback
Execute tests on generated code and iterate until passing
Open skill

