/qcsd-refinement-swarm
Use when running Sprint Refinement sessions with SFDIPOT product factors, generating BDD scenarios, or validating requirements in the QCSD Refinement phase.
$ npx -y skills add proffesor-for-testing/agentic-qe --skill qcsd-refinement-swarm --agent claude-codeHow it fires
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/qcsd-refinement-swarm
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Use when running Sprint Refinement sessions with SFDIPOT product factors, generating BDD scenarios, or validating requirements in the QCSD Refinement phase.
SKILL.md
qcsd-refinement-swarm.SKILL.mdname: qcsd-refinement-swarm
description: "Use when running Sprint Refinement sessions with SFDIPOT product factors, generating BDD scenarios, or validating requirements in the QCSD Refinement phase."
category: qcsd-phases
priority: critical
version: 1.0.0
tokenEstimate: 3200
# DDD Domain Mapping (from QCSD-AGENTIC-QE-MAPPING-FRAMEWORK.md)
domains:
primary:
- domain: requirements-validation
agents: [qe-product-factors-assessor, qe-bdd-generator, qe-requirements-validator]
conditional:
- domain: contract-testing
agents: [qe-contract-validator]
- domain: code-intelligence
agents: [qe-impact-analyzer, qe-dependency-mapper]
- domain: enterprise-integration
agents: [qe-middleware-validator, qe-odata-contract-tester, qe-sod-analyzer]
transformation:
- domain: test-generation
agents: [qe-test-idea-rewriter]
# Agent Inventory
agents:
core: [qe-product-factors-assessor, qe-bdd-generator, qe-requirements-validator]
conditional: [qe-contract-validator, qe-impact-analyzer, qe-dependency-mapper, qe-middleware-validator, qe-odata-contract-tester, qe-sod-analyzer]
transformation: [qe-test-idea-rewriter]
total: 10
sub_agents: 0
skills: [context-driven-testing, testability-scoring, risk-based-testing]
# Execution Models (Task Tool is PRIMARY)
execution:
primary: task-tool
alternatives: [mcp-tools, cli]
swarm_pattern: true
parallel_batches: 3
last_updated: 2026-02-02
enforcement_level: strict
tags: [qcsd, refinement, sfdipot, bdd, gherkin, requirements, swarm, parallel, ddd]
trust_tier: 3
validation:
schema_path: schemas/output.json
validator_path: scripts/validate-config.json
eval_path: evals/qcsd-refinement-swarm.yamlQCSD Refinement Swarm v1.0
Shift-left quality engineering swarm for Sprint Refinement sessions.
---
Overview
The Refinement Swarm takes user stories that passed Ideation and prepares them for Sprint commitment using SFDIPOT product factors, BDD scenarios, and INVEST validation. It renders a READY / CONDITIONAL / NOT-READY decision.
QCSD Phase Positioning
| Phase | Swarm | Decision | When | |-------|-------|----------|------| | Ideation | qcsd-ideation-swarm | GO / CONDITIONAL / NO-GO | PI/Sprint Planning | | **Refinement** | **qcsd-refinement-swarm** | **READY / CONDITIONAL / NOT-READY** | **Sprint Refinement** | | Development | qcsd-development-swarm | SHIP / CONDITIONAL / HOLD | During Sprint | | Verification | qcsd-cicd-swarm | RELEASE / REMEDIATE / BLOCK | Pre-Release / CI-CD | | Production | qcsd-production-swarm | HEALTHY / DEGRADED / CRITICAL | Post-Release |
Parameters
- `STORY_CONTENT`: User story with acceptance criteria (required)
- `OUTPUT_FOLDER`: Where to save reports (default: `${PROJECT_ROOT}/Agentic QCSD/refinement/`)
---
ENFORCEMENT RULES - READ FIRST
| Rule | Enforcement | |------|-------------| | **E1** | MUST spawn ALL THREE core agents in Step 2. | | **E2** | MUST put all parallel Task calls in a SINGLE message. | | **E3** | MUST STOP and WAIT after each batch. | | **E4** | MUST spawn conditional agents if flags are TRUE. | | **E5** | MUST apply READY/CONDITIONAL/NOT-READY logic exactly. | | **E6** | MUST generate the full report structure. | | **E7** | Each agent MUST read its reference files before analysis. | | **E8** | MUST apply qe-test-idea-rewriter transformation in Step 8. | | **E9** | MUST execute Step 7 learning persistence. |
---
Step Execution Protocol
Execute steps sequentially by reading each step file with the Read tool.
Steps
1. **Flag Detection** -- `steps/01-flag-detection.md` -- Analyze story content, evaluate all 7 flags 2. **Core Agents** -- `steps/02-core-agents.md` -- Spawn qe-product-factors-assessor, qe-bdd-generator, qe-requirements-validator 3. **Batch 1 Results** -- `steps/03-batch1-results.md` -- Wait and extract metrics 4. **Conditional Agents** -- `steps/04-conditional-agents.md` -- Spawn flagged agents 5. **Decision Synthesis** -- `steps/05-decision-synthesis.md` -- Apply READY/CONDITIONAL/NOT-READY logic 6. **Report Generation** -- `steps/06-report-generation.md` -- Generate refinement report 7. **Learning Persistence** -- `steps/07-learning-persistence.md` -- Store findings to memory 8. **Transformation** -- `steps/08-transformation.md` -- Run test idea rewriter on all test ideas 9. **Final Output** -- `steps/09-final-output.md` -- Display completion summary
Execution Instructions
1. Use the Read tool to load the current step file 2. Execute the step's instructions completely 3. Verify all success criteria are met 4. Pass output as context to next step 5. If a step fails, halt and report
Resume Support
To resume from a specific step: specify `--from-step N`.
---
Agent Inventory
| Agent | Type | Domain | Batch | |-------|------|--------|-------| | qe-product-factors-assessor | Core | requirements-validation | 1 | | qe-bdd-generator | Core | requirements-validation | 1 | | qe-requirements-validator | Core | requirements-validation | 1 | | qe-contract-validator | Conditional (HAS_API) | contract-testing | 2 | | qe-impact-analyzer | Conditional (HAS_REFACTORING) | code-intelligence | 2 | | qe-dependency-mapper | Conditional (HAS_DEPENDENCIES) | code-intelligence | 2 | | qe-middleware-validator | Conditional (HAS_MIDDLEWARE) | enterprise-integration | 2 | | qe-odata-contract-tester | Conditional (HAS_SAP_INTEGRATION) | enterprise-integration | 2 | | qe-sod-analyzer | Conditional (HAS_AUTHORIZATION) | enterprise-integration | 2 | | qe-test-idea-rewriter | Transformation (always) | test-generation | 3 |
**Total: 10 agents (3 core + 6 conditional + 1 transformation)**
---
Key Principle
**Refinement quality determines sprint success. This swarm ensures stories are testable, complete, and ready for development commitment.**
Read more
name: qcsd-refinement-swarm
description: "Use when running Sprint Refinement sessions with SFDIPOT product factors, generating BDD scenarios, or validating requirements in the QCSD Refinement phase."
category: qcsd-phases
priority: critical
version: 1.0.0
tokenEstimate: 3200
# DDD Domain Mapping (from QCSD-AGENTIC-QE-MAPPING-FRAMEWORK.md)
domains:
primary:
- domain: requirements-validation
agents: [qe-product-factors-assessor, qe-bdd-generator, qe-requirements-validator]
conditional:
- domain: contract-testing
agents: [qe-contract-validator]
- domain: code-intelligence
agents: [qe-impact-analyzer, qe-dependency-mapper]
- domain: enterprise-integration
agents: [qe-middleware-validator, qe-odata-contract-tester, qe-sod-analyzer]
transformation:
- domain: test-generation
agents: [qe-test-idea-rewriter]
# Agent Inventory
agents:
core: [qe-product-factors-assessor, qe-bdd-generator, qe-requirements-validator]
conditional: [qe-contract-validator, qe-impact-analyzer, qe-dependency-mapper, qe-middleware-validator, qe-odata-contract-tester, qe-sod-analyzer]
transformation: [qe-test-idea-rewriter]
total: 10
sub_agents: 0
skills: [context-driven-testing, testability-scoring, risk-based-testing]
# Execution Models (Task Tool is PRIMARY)
execution:
primary: task-tool
alternatives: [mcp-tools, cli]
swarm_pattern: true
parallel_batches: 3
last_updated: 2026-02-02
enforcement_level: strict
tags: [qcsd, refinement, sfdipot, bdd, gherkin, requirements, swarm, parallel, ddd]
trust_tier: 3
validation:
schema_path: schemas/output.json
validator_path: scripts/validate-config.json
eval_path: evals/qcsd-refinement-swarm.yamlQCSD Refinement Swarm v1.0
Shift-left quality engineering swarm for Sprint Refinement sessions.
---
Overview
The Refinement Swarm takes user stories that passed Ideation and prepares them for Sprint commitment using SFDIPOT product factors, BDD scenarios, and INVEST validation. It renders a READY / CONDITIONAL / NOT-READY decision.
QCSD Phase Positioning
| Phase | Swarm | Decision | When | |-------|-------|----------|------| | Ideation | qcsd-ideation-swarm | GO / CONDITIONAL / NO-GO | PI/Sprint Planning | | **Refinement** | **qcsd-refinement-swarm** | **READY / CONDITIONAL / NOT-READY** | **Sprint Refinement** | | Development | qcsd-development-swarm | SHIP / CONDITIONAL / HOLD | During Sprint | | Verification | qcsd-cicd-swarm | RELEASE / REMEDIATE / BLOCK | Pre-Release / CI-CD | | Production | qcsd-production-swarm | HEALTHY / DEGRADED / CRITICAL | Post-Release |
Parameters
- `STORY_CONTENT`: User story with acceptance criteria (required)
- `OUTPUT_FOLDER`: Where to save reports (default: `${PROJECT_ROOT}/Agentic QCSD/refinement/`)
---
ENFORCEMENT RULES - READ FIRST
| Rule | Enforcement | |------|-------------| | **E1** | MUST spawn ALL THREE core agents in Step 2. | | **E2** | MUST put all parallel Task calls in a SINGLE message. | | **E3** | MUST STOP and WAIT after each batch. | | **E4** | MUST spawn conditional agents if flags are TRUE. | | **E5** | MUST apply READY/CONDITIONAL/NOT-READY logic exactly. | | **E6** | MUST generate the full report structure. | | **E7** | Each agent MUST read its reference files before analysis. | | **E8** | MUST apply qe-test-idea-rewriter transformation in Step 8. | | **E9** | MUST execute Step 7 learning persistence. |
---
Step Execution Protocol
Execute steps sequentially by reading each step file with the Read tool.
Steps
1. **Flag Detection** -- `steps/01-flag-detection.md` -- Analyze story content, evaluate all 7 flags 2. **Core Agents** -- `steps/02-core-agents.md` -- Spawn qe-product-factors-assessor, qe-bdd-generator, qe-requirements-validator 3. **Batch 1 Results** -- `steps/03-batch1-results.md` -- Wait and extract metrics 4. **Conditional Agents** -- `steps/04-conditional-agents.md` -- Spawn flagged agents 5. **Decision Synthesis** -- `steps/05-decision-synthesis.md` -- Apply READY/CONDITIONAL/NOT-READY logic 6. **Report Generation** -- `steps/06-report-generation.md` -- Generate refinement report 7. **Learning Persistence** -- `steps/07-learning-persistence.md` -- Store findings to memory 8. **Transformation** -- `steps/08-transformation.md` -- Run test idea rewriter on all test ideas 9. **Final Output** -- `steps/09-final-output.md` -- Display completion summary
Execution Instructions
1. Use the Read tool to load the current step file 2. Execute the step's instructions completely 3. Verify all success criteria are met 4. Pass output as context to next step 5. If a step fails, halt and report
Resume Support
To resume from a specific step: specify `--from-step N`.
---
Agent Inventory
| Agent | Type | Domain | Batch | |-------|------|--------|-------| | qe-product-factors-assessor | Core | requirements-validation | 1 | | qe-bdd-generator | Core | requirements-validation | 1 | | qe-requirements-validator | Core | requirements-validation | 1 | | qe-contract-validator | Conditional (HAS_API) | contract-testing | 2 | | qe-impact-analyzer | Conditional (HAS_REFACTORING) | code-intelligence | 2 | | qe-dependency-mapper | Conditional (HAS_DEPENDENCIES) | code-intelligence | 2 | | qe-middleware-validator | Conditional (HAS_MIDDLEWARE) | enterprise-integration | 2 | | qe-odata-contract-tester | Conditional (HAS_SAP_INTEGRATION) | enterprise-integration | 2 | | qe-sod-analyzer | Conditional (HAS_AUTHORIZATION) | enterprise-integration | 2 | | qe-test-idea-rewriter | Transformation (always) | test-generation | 3 |
**Total: 10 agents (3 core + 6 conditional + 1 transformation)**
---
Key Principle
**Refinement quality determines sprint success. This swarm ensures stories are testable, complete, and ready for development commitment.**
AI-powered quality engineering agents that generate tests, find coverage gaps, detect flaky tests, and learn your codebase patterns — across 11 coding agent platforms.
Repo: proffesor-for-testing/agentic-qe
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