Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.
日本語の概要は準備中です。原文の説明を表示しています。
Use when running Quality Criteria sessions during PI/Sprint planning with HTSM v6.3, Risk Storming, or Testability analysis in the QCSD Ideation phase.
日本語の概要は準備中です。原文の説明を表示しています。
実行スコア 未検証
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Shift-left quality engineering swarm for PI Planning and Sprint Planning.
The Ideation Swarm assesses stories and URLs before development begins, using HTSM v6.3 quality criteria, Risk Storming, and Testability analysis. It renders a GO / CONDITIONAL / NO-GO decision and is the first gate in the QCSD lifecycle.
| 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 |
URL: Website to analyze (required for URL mode)OUTPUT_FOLDER: Where to save reports (default: ${PROJECT_ROOT}/Agentic QCSD/{domain}/)/a11y-ally follow-uphtml_output: true| Rule | Enforcement |
|---|---|
| E1 | You MUST spawn ALL THREE core agents (qe-quality-criteria-recommender, qe-risk-assessor, qe-requirements-validator) in Step 2. No exceptions. |
| E2 | You MUST put all parallel Task calls in a SINGLE message. |
| E3 | You MUST STOP and WAIT after each batch. No proceeding early. |
| E4 | You MUST spawn conditional agents if flags are TRUE. No skipping. |
| E5 | You MUST apply GO/CONDITIONAL/NO-GO logic exactly as specified in Step 5. |
| E6 | You MUST generate the full report structure. No abbreviated versions. |
| E7 | Each agent MUST read its reference files before analysis. |
| E8 | You MUST execute Step 7 learning persistence. No skipping. |
PROHIBITED BEHAVIORS:
This skill uses a micro-file step architecture. Each step is a self-contained file loaded one at a time to avoid "lost in the middle" context degradation.
Execute steps sequentially by reading each step file with the Read tool.
steps/01-flag-detection.md -- Fetch URL content (browser cascade), detect all 7 flags (HAS_UI, HAS_SECURITY, HAS_UX, HAS_VIDEO, HAS_MIDDLEWARE, HAS_SAP_INTEGRATION, HAS_AUTHORIZATION)steps/02-core-agents.md -- Spawn qe-quality-criteria-recommender, qe-risk-assessor, qe-requirements-validator in parallelsteps/03-batch1-results.md -- Wait for core agents, extract all metricssteps/04-conditional-agents.md -- Spawn flagged conditional agents in parallelsteps/05-decision-synthesis.md -- Apply GO/CONDITIONAL/NO-GO logicsteps/06-report-generation.md -- Generate executive summary and full reportsteps/07-learning-persistence.md -- Store findings to memory, save persistence record, include video follow-up recommendationsteps/08-final-output.md -- Display completion summary with all scores and follow-up recommendationsRead({ file_path: ".claude/skills/qcsd-ideation-swarm/steps/01-flag-detection.md" }))To resume from a specific step: specify --from-step N and the orchestrator will
skip to step N. Ensure you have the required prerequisite data from prior steps.
| Agent | Type | Domain | Batch |
|---|---|---|---|
| qe-quality-criteria-recommender | Core (always) | requirements-validation | 1 |
| qe-risk-assessor | Core (always) | coverage-analysis | 1 |
| qe-requirements-validator | Core (always) | requirements-validation | 1 |
| qe-accessibility-auditor | Conditional (HAS_UI) | visual-accessibility | 2 |
| qe-security-auditor | Conditional (HAS_SECURITY) | security-compliance | 2 |
| qe-qx-partner | Conditional (HAS_UX) | cross-domain | 2 |
| qe-middleware-validator | Conditional (HAS_MIDDLEWARE) | enterprise-integration | 2 |
| qe-sap-rfc-tester | Conditional (HAS_SAP_INTEGRATION) | enterprise-integration | 2 |
| qe-sod-analyzer | Conditional (HAS_AUTHORIZATION) | enterprise-integration | 2 |
Total: 9 agents (3 core + 6 conditional)
Note: The Ideation swarm has 8 steps (not 9) because it has no separate final
analysis agent step. The HAS_VIDEO flag triggers a follow-up recommendation for
/a11y-ally but does not spawn an additional agent.
| Metric | GO | CONDITIONAL | NO-GO |
|---|---|---|---|
| Testability Score | >= 70% | 40 - 69% | < 40% |
| Risk Score | LOW/MEDIUM | HIGH (mitigatable) | CRITICAL |
| Requirements Completeness | >= 80% | 50 - 79% | < 50% |
| Quality Criteria Coverage | >= 7/10 categories | 4-6/10 categories | < 4/10 categories |
| Agent | Report Filename | Step |
|---|---|---|
| qe-quality-criteria-recommender | 02-quality-criteria.md | 2 |
| qe-risk-assessor | 03-risk-assessment.md | 2 |
| qe-requirements-validator | 04-requirements-validation.md | 2 |
| qe-accessibility-auditor | 05-accessibility-audit.md | 4 |
| qe-security-auditor | 06-security-audit.md | 4 |
| qe-qx-partner | 07-ux-assessment.md | 4 |
| qe-middleware-validator | 08-middleware-assessment.md | 4 |
| qe-sap-rfc-tester | 09-sap-assessment.md | 4 |
| qe-sod-analyzer | 10-sod-compliance.md | 4 |
| Learning Persistence | 11-learning-persistence.json | 7 |
| Synthesis | 01-executive-summary.md | 6 |
| Model | When to Use | Agent Spawn |
|---|---|---|
| Task Tool (PRIMARY) | Claude Code sessions | Task({ subagent_type, run_in_background: true }) |
| MCP Tools | MCP server available | fleet_init({}) / task_submit({}) |
| CLI | Terminal/scripts | swarm init / agent spawn |
Quality is built in from the start, not tested in at the end. This swarm ensures stories are viable, testable, and risk-assessed before any code is written.
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Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.
日本語の概要は準備中です。原文の説明を表示しています。
WCAG 2.2 compliance testing, screen reader validation, and inclusive design verification. Use when ensuring legal compliance (ADA, Section 508), testing for disabilities, or building accessible applications for 1 billion disabled users globally.
日本語の概要は準備中です。原文の説明を表示しています。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
日本語の概要は準備中です。原文の説明を表示しています。
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
日本語の概要は準備中です。原文の説明を表示しています。
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
日本語の概要は準備中です。原文の説明を表示しています。
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
日本語の概要は準備中です。原文の説明を表示しています。