muratcankoylanCommunity·24 Agent Skills Included

Agent-Skills-for-Context-Engineering

Teach AI agents to manage context, memory, and multi-agent workflows

Teaches AI agents how to manage context windows, memory, tools, and multi-agent coordination in production systems. Covers context compression, degradation diagnosis, evaluation rubrics, long-horizon prompting, and self-improving agent loops. Eliminates trial-and-error prompt tuning by giving agents proven patterns for building reliable autonomous workflows.

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npx skills add muratcankoylan/Agent-Skills-for-Context-Engineering --all -g -y

Available:

Tells the AI agent how the skill collection is organized, which validation gates to run before changing skills, and the workspace rules for tone, approvals, and research loops.

All Skills in This Repository (24)

Pure Emerald Level Indicators

📦 In Repo

muratcankoylan

context-engineering-collection

Centralizes best practices for AI agent context engineering.

skill-template

Create new Skill units with a standardized SKILL.md template and YAML frontmatter.

digital-brain

Manage a modular personal knowledge system with append-only JSONL, YAML, and MD data.

reasoning-trace-optimizer

Analyze interleaved thinking traces to detect failure patterns and optimize prompts.

book-sft-pipeline

Convert ePub books into JSONL SFT datasets and train LoRA style models.

comprehensive-research-agent

Organizes source-driven research into a synthesized, citable report.

multi-agent-patterns

Coordinate multi-agent tasks with explicit handoffs and context isolation.

bdi-mental-states

Translate agent cognition prompts into RDF-based BDI mental states linked to world states.

context-degradation

Diagnose context degradation patterns and provide mitigation strategies for agent systems.

context-compression

Summarize long-running agent sessions while tracking modified files and decisions.

memory-systems

Persist agent memory across sessions using multi-layer architecture and temporal knowledge graphs.

advanced-evaluation

Automate LLM output evaluation with direct scoring and pairwise comparisons.

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Frequently Asked Questions

FAQPage Schema

How to install Agent-Skills-for-Context-Engineering?▼

Run `npx skills add muratcankoylan/Agent-Skills-for-Context-Engineering --all -g -y` in your terminal to install all skills globally.

What is context engineering for AI agents?▼

It is the practice of curating everything that enters a model's context window, like prompts, tools, and documents, so the agent gets maximum signal within its limited attention budget.

Which AI coding tools work with these skills?▼

The skills are platform-agnostic and work with Claude Code, Cursor, Codex, GitHub Copilot, and any tool that supports the Agent Skills standard.

How do these skills improve multi-agent systems?▼

They teach proven patterns for supervisor and swarm architectures, context isolation between agents, memory sharing, and evaluation gates that prevent coordination failures.

Do I need to write code to use these skills?▼

No. Once installed, your AI agent reads and applies the skills automatically when your task matches, using plain-English requests.