Agent skill · Code Review & Quality

context-fundamentals

This skill should be used to explain or reason about the foundational concepts of context engineering: what context is, the anatomy of a context window, how attention mechanics work, the U-shaped attention curve, why context quality matters more than quantity, and the mental models needed to interpret every other context-engineering decision. Use this for conceptual explanation, onboarding, and background reading. Route operational work to the specialized skills: debugging attention failures goes to context-degradation, token-efficiency work goes to context-optimization, conversation summariza

guanyanggithub.com/guanyangGitHub ↗
claude-codeships scriptsMIT
Install
npx skills add guanyang/open-agent-hub --skill context-fundamentals --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 3
SKILL.md size: 17 KB
Bundled scripts: yes
Path: skills/context-fundamentals/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 940
Language: TypeScript

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Context Engineering Fundamentals Context is the complete state available to a language model at inference time: system instructions, tool definitions, retrieved documents, message history, and tool outputs. Context engineering is the discipline of curating the smallest high-signal token set that maximizes the likelihood of desired outcomes. This skill is the conceptual foundation that every other skill in the collection builds on. It explains what context is, how attention mechanics work, why context quality matters more than quantity, and the mental models needed to interpret every other context-engineering decision. It does not own operational work: debugging attention failures belongs to `context-degradation`, token-efficiency tactics belong to `context-optimization`, conversation summarization belongs to `context-compression`, file-based offloading belongs to `filesystem-context`, and project-shape decisions belong to `project-development`. ## When to Activate Activate this skill when the work is conceptual: - Explaining what context is and how attention mechanics constrain agent behavior. - Onboarding new contributors who need the mental models before diving into operational

What's inside
Steps it walks through
  1. When to Activate
  2. Core Concepts
  3. Detailed Topics
  4. The Anatomy of Context
  5. Context Windows and Attention Mechanics
  6. Context Quality Versus Quantity
  7. Practical Guidance
  8. Reasoning About a Context Decision
  9. Reading Order For New Contributors
  10. Examples
  11. Guidelines
  12. Gotchas
  13. Integration
  14. References
Ships with 2 files
  • references/context-components.md
  • scripts/context_manager.py
More from open-agent-hub
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About this skill
What does the context-fundamentals skill do?

This skill should be used to explain or reason about the foundational concepts of context engineering: what context is, the anatomy of a context window, how attention mechanics work, the U-shaped attention curve, why context quality matters more than quantity, and the mental models needed to interpret every other context-engineering decision. Use this for conceptual explanation, onboarding, and background reading. Route operational work to the specialized skills: debugging attention failures goes to context-degradation, token-efficiency work goes to context-optimization, conversation summariza

How do I install it?

Run `npx skills add guanyang/open-agent-hub --skill context-fundamentals --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From guanyang/open-agent-hub, a repository with 940 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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