agentic-swe-kit

Use when designing, building, evaluating, or operating AI agent systems in production — agent architecture, orchestration patterns, RAG pipelines, evaluation, observability, guardrails, and domain-specific deployment.

Use when starting, reviewing, or building any production-grade software or AI-native system. Orchestrates the full 20-phase production lifecycle, routes to the right domain skills at each phase, and guides the agent through every engineering layer from cognitive design to continuous learning.

Use when designing, evaluating, or debugging data-intensive systems — storage engines, replication, partitioning, transactions, distributed consistency, batch/stream processing, or encoding.

Use when designing, implementing, or debugging distributed services — architecture choices, consistency trade-offs, fault tolerance, coordination, naming, and security for multi-node systems.

Use when a coding agent must make architectural, quality, or design decisions during implementation — calibrating trade-offs, communicating honestly, and maintaining integrity across iterations.

Use when making dependency management decisions, drawing component boundaries, applying SOLID principles, designing layered architectures, or evaluating whether a structural decision keeps options open vs. locks them in.

Use when designing, reviewing, or building production systems — architecture decisions, integration points, stability patterns, capacity planning, observability, and operations.

Security engineering principles: threat modeling, cryptography, access control, privacy, secure development, physical/operational security, and economics of trust. Covers adversarial thinking, protocol design, tamper resistance, and assurance.