Context Engineering Collection

muratcankoylan/agent-skills-for-context-engineering

If you're building agent systems that keep running into context limits or losing track of state across conversations, this collection covers the architecture patterns that actually matter. The filesystem-as-memory approach is smarter than you'd expect, multi-agent coordination patterns focus on context isolation rather than role-playing, and the evaluation guidance keeps you honest about what's actually working. The latent briefing section on KV cache sharing between orchestrators and workers is legitimately novel. It's opinionated about things like tool consolidation and when to use compression, which saves you from rediscovering these lessons the hard way. Treat it as a reference when you're past the prototype stage and need production reliability.

GitHub stars: 16.5K
last updated: May 26, 2026

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Install

$ npx -y skills add muratcankoylan/agent-skills-for-context-engineering --skill context-engineering-collection --agent claude-code

Installs into .claude/skills of the current project.

Files

Agent Skills for Context Engineering

This collection provides structured guidance for building production-grade AI agent systems through effective context engineering.

When to Activate

Activate these skills when:

Building new agent systems from scratch
Optimizing existing agent performance
Debugging context-related failures
Designing multi-agent architectures
Creating or evaluating tools for agents
Implementing memory and persistence layers
Designing autonomous research or evaluation harnesses

Skill Map

Foundational Context Engineering

Understanding Context Fundamentals Context is not just prompt text—it is the complete state available to the language model at inference time, including system instructions, tool definitions, retrieved documents, message history, and tool outputs. Effective context engineering means understanding what information truly matters for the task at hand and curating that information for maximum signal-to-noise ratio.

SKILL.md on GitHub