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Ai context engine

Skill ebarti/skills/ai-context-engine

📚 Agent skills distilled from technical books — AI Engineering, Context Engineering, Designing Data-Intensive Applications, and more. Agent-agnostic, plain Markdown. Give your AI agent a bookshelf.

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npx -y skills add ebarti/skills --skill ai-context-engine

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The full Context Engine architecture: dual RAG (procedural + factual), Pinecone-based ingestion, the Planner / Executor / Tracer triad, specialist agents (Context Librarian, Researcher, Writer), the Agent Registry, production hardening (dependency injection, logging, modularization), plus an appendix-style reference guide. Use this skill when: - Building a context engine from scratch - Choosing between procedural RAG (blueprints) and factual RAG (evidence) - Setting up Pinecone ingestion (chunking, embedding, namespaces) - Designing a Planner-driven execution flow with traceability - Adding or refactoring specialist agents - Building or extending an Agent Registry - Hardening a notebook prototype for production (DI, logging, modularization) - Looking up the engine's commons library reference (helpers/agents/registry/engine/utils)

SKILL.md

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AI Context Engine

Knowledge from "Context Engineering for Multi-Agent Systems" (Chapters 3-5 + Appendix A). The full architecture and hardening of the glass-box Context Engine.

Quick Start

  1. Check guidelines.md to find which files to load
  2. Load only relevant files (each topic has knowledge.md, rules.md, examples.md)
  3. Apply guidance to your work

Contents

References

CategoryPurpose
dual-ragProcedural vs factual RAG, context library vs knowledge base
rag-ingestionPinecone setup, token-aware chunking, embeddings, upsert
engine-componentsPlanner, Executor, Execution Tracer (the engine triad)
specialist-agentsContext Librarian, Researcher, Writer (initial + hardened)
agent-registryCapability descriptions, get_handler, dependency injection
hardeningDI, structured logging, proactive context mgmt, modularization
engine-referenceAppendix-style reference guide for the commons library

Workflows

WorkflowPurpose
workflows/build-context-engine.mdFull engine build (dual RAG → triad → agents → registry → run)
workflows/setup-rag-pipeline.mdPinecone ingestion (chunk → embed → upsert)
workflows/harden-engine.mdTake prototype to production (DI, logging, modularization)

Guidelines

See guidelines.md for task-based file selection.

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