Create risk-based quality and test plans for Agentic QE changes. Use when scoping a feature, translating requirements into verification work, selecting QE specialties, assessing testability, or deciding which `.claude/agents/v3/qe-*.md` capabilities should inform a task. Do not use merely to execute an already-defined test command.
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Run score Not tested
See how to installReview the instructions the agent will receive before you install.
AGENTS.md, the requested change, and the affected public boundaries.Task, SendMessage, or
hook syntax into Codex actions.Prefer evidence from repository code and configuration over generic test checklists. Keep the selected fleet small and explain each specialty’s purpose.
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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.
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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.
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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.
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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.
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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.
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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.
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