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davidbirchall/squad-skills-ai-engineering

v0.2.0

AI engineering skills for LLM-powered applications and agent systems: LLM integration, prompt engineering, agent design and orchestration, tool and MCP integration, context engineering, retrieval-augmented generation, evaluation, testing, security, and observability.

agent-design

Designing a single LLM agent in a TypeScript/Node/NestJS backend - deciding between a single call, a fixed workflow, and an agent; the agent loop; goals and explicit stop conditions; step, token, time, and cost budgets; state and memory; planning; human-in-the-loop approval; failure handling; single-responsibility agents; and autonomy levels. Provider-agnostic. Load when deciding whether to build an agent, designing an agent loop, setting limits, or adding approvals and recovery.

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