/eval-workflow
Run evaluation tests against a multi-agent workflow to assess orchestration quality and failure archetype resistance
Claude Code
$ npx -y skills add jmagly/aiwg --skill eval-workflow --agent claude-code
Codex
$ npx skills add jmagly/aiwg --skill eval-workflow -a codex -y
Cursor
$ npx skills add jmagly/aiwg --skill eval-workflow -a cursor -y
Gemini CLI
$ npx skills add jmagly/aiwg --skill eval-workflow -a gemini-cli -y
GitHub Copilot
$ npx skills add jmagly/aiwg --skill eval-workflow -a github-copilot -y
OpenCode
$ npx skills add jmagly/aiwg --skill eval-workflow -a opencode -y
Windsurf
$ npx skills add jmagly/aiwg --skill eval-workflow -a windsurf -y
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
Reusable project context and specialist workflows for the AI tools you already use. Plan software, coordinate specialist reviews, prepare campaigns, investigate incidents, organize research, curate media, and maintain operational knowledge.
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Questions about eval-workflow.
- Which coding agents can use eval-workflow?
- eval-workflow installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.

