# muratcankoylan/Agent-Skills-for-Context-Engineering

A comprehensive collection of Agent Skills for context engineering, multi-agent architectures, and production agent systems. Use when building, optimizing, or debugging agent systems that require effective context management.

Repository: https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering
Canonical: https://ross.abutalabs.com/products/agent-skills-for-context-engineering
Language: Python
License: MIT
License Family: permissive
Last push: 2026-08-19T01:55:00+00:00

## Health v2 (maintenance only)
Score: 73/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 73, longevity 18
- inputs: {"age_days": 255, "days_push": 15, "days_rel": 103, "gap_med": 74.0, "n_releases_24m": 3}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 17838, forks 1475 (observed 2026-08-28T04:11:20.466993+00:00)

## What it is
A curated collection of Agent Skills (documentation/playbooks) for context engineering and multi-agent architecture, written in Python and MIT-licensed. It teaches context curation, degradation patterns, compression, and agent operating loops for production agent systems.

## Use cases
- learn context engineering for LLM agents
- design multi-agent architectures
- debug context degradation in agent systems
- compress long-running agent session context
- build production-grade AI agent harnesses
- evaluate agent behavior across platforms

## When to choose
- you are building or optimizing LLM agent systems and need context management guidance
- you want vetted patterns for multi-agent orchestration
- you need educational material on context window limitations

## When to avoid
- you need runnable agent framework code rather than skills/documentation
- you are not working with LLM-based agents

## Facets
- artifact type: learning-resource
- maturity: active
- function: agent-framework, prompt-engineering, rag, llm-training
- domain: large-language-models, developer-tools, tutorials
- platform: python, cross-platform
- tags: context-engineering, agent-skills, multi-agent, documentation, awesome-lists, ai-agents, retrieval-augmented-generation

## Member repositories
- muratcankoylan/Agent-Skills-for-Context-Engineering (main) score 73

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:20.466993+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:02:26.494056+00:00, confidence not recorded.
  - readme: https://github.com/muratcankoylan/Agent-Skills-for-Context-Engineering (fetched 2026-08-28T04:11:20.466993+00:00, sha 1ddd1b586caf)
- Data as of 2026-08-30T08:39:29.467469+00:00.