Guide · Agent skill
How to use the Context Engineering Fundamentals agent skill
Updated · written with AI from the project's own documentation and checked against our catalogue data
The Context Engineering Fundamentals skill (named context-fundamentals) gives an AI agent the background needed to explain how language models use their context. It covers what context is, how a context window is made up, how attention works, and why less but better-chosen context often beats more. This guide shows you how to install it, how to ask for it with natural requests, what it needs, and which other skills handle the hands-on problems it does not.
Context Engineering Fundamentalsmuratcankoylan/Agent-Skills-for-Context-Engineering · MIT Download the skill Quick start
- 1Download the ZIP. Get the context-fundamentals ZIP file from the skill's page on this site.
- 2Unzip into the right folder. Unzip it into ~/.claude/skills/ for personal use, or into .claude/skills/ in a project to limit it to that project.
- 3Or upload it in the Claude apps. In the Claude apps, go to Settings, then Capabilities, then Skills, and upload the ZIP.
- 4Ask a conceptual question. Describe what you want explained in plain language, such as what a context window is or how the U-shaped attention curve works.
- 5Route hands-on problems elsewhere. If you need to debug, cut token costs or summarize a session, ask for the specialized skill that handles that work.
What the context-fundamentals skill makes the agent do
Once installed, the agent can explain what 'context' means for a language model: everything the model can see at once, including system instructions, tool definitions, retrieved documents, message history and tool outputs. It treats context as a finite attention budget rather than a storage bin, so every added token competes for the model's attention.
The skill is built for conceptual reasoning. It explains the U-shaped attention curve, which describes information in the middle of a long context being recalled less reliably than information at the start or end. It also explains why context quality matters more than quantity, and it gives the agent a set of mental models for judging other context decisions.
How to install the skill
You can install the skill in one of three ways. Download the ZIP file from the skill's page on this site, then pick the option that fits how you work.
For Claude Code, unzip the download into your personal skills folder at ~/.claude/skills/. To limit the skill to one project, unzip it into the .claude/skills/ folder inside that project instead.
In the Claude apps, upload the ZIP under Settings, then Capabilities, then Skills.
- Personal use across projects: unzip into ~/.claude/skills/
- Single project: unzip into .claude/skills/ inside the project
- Claude apps: upload the ZIP under Settings → Capabilities → Skills
How to trigger the skill with natural requests
You do not need a special command. Ask a conceptual question in plain language and the agent can choose to use the skill. The skill's description says it is meant for explanation, onboarding and background reading, so phrasing your request that way helps.
Requests that work well are about understanding: asking what a context window is, why a model seems to forget something in the middle of a long prompt, or how to explain context to a new team member.
- What is a context window and what counts toward it?
- Explain the U-shaped attention curve to me like I am new to LLMs.
- Help me onboard a new contributor to our context-engineering practices.
- Why does less but better-chosen context often work better than more?
Examples of what you can ask for
A useful test is to ask for an explanation you can reuse. For example, you can ask the agent to describe the anatomy of a context window using a system prompt, tool definitions, documents and message history, then check whether the explanation matches your own system.
Writers and students can ask for a grounded account of how attention constrains agent behaviour. Developers can ask for the reasoning behind a design trade-off before they pick a specific technique.
- Ask for a one-page explainer on context for a product manager.
- Ask why placing critical instructions at the start and end of a prompt is recommended.
- Ask what 'altitude' means for system prompt instructions and why too-low or too-high altitude causes problems.
What it needs and safety notes
The SKILL.md file itself needs no software, no API keys, no accounts and no external services. The skill's files do not indicate any API keys or accounts. The skill does not use the network.
The skill includes a script, scripts/context_manager.py, that runs as a demo. Python 3 is only needed if you choose to run that script. The script uses a rough character-ratio estimate rather than a real tokenizer and is labelled demo-only, so do not use its numbers as precise token counts. Read any bundled script before you run it.
- Python 3: only needed to run scripts/context_manager.py
- No API keys, accounts or external services are indicated in the files
- Network use: none
- Token figures from the script are rough estimates, not exact counts
Tips and when to use other skills
This skill explains concepts but does not fix problems. If you need hands-on help, use the specialized skill that owns that task. Debugging attention failures goes to context-degradation. Token-efficiency work goes to context-optimization. Summarizing a long conversation goes to context-compression. Offloading large tool outputs or keeping a scratchpad goes to filesystem-context. Deciding the shape of an LLM project goes to project-development.
Keep your questions focused. The skill is most useful when you ask about one mental model at a time, such as attention budgets or instruction altitude.
- Debugging lost-in-the-middle failures: context-degradation
- Cutting token cost: context-optimization
- Summarizing a long session: context-compression
- Large tool outputs and scratchpads: filesystem-context
- Project and pipeline design: project-development
What people use it for
- Onboarding a new developer to context-engineering concepts before they tune prompts.
- Preparing a team explainer on why less, better-chosen context often works better.
- Writing documentation that grounds operational advice in how attention works.
- Studying how model attention constrains agent behaviour for a class or article.
Frequently asked questions
How do I install the context-fundamentals skill?
Download the ZIP from the skill's page on this site. Unzip it into ~/.claude/skills/ for personal use or into .claude/skills/ in a project, or upload it in the Claude apps under Settings, then Capabilities, then Skills.
What do I need to run the context-fundamentals skill?
The SKILL.md file needs no software, API keys or accounts. Python 3 is only needed if you want to run the bundled scripts/context_manager.py demo, which uses a rough character-ratio estimate.
Is the context-fundamentals skill free?
The skill is published under the MIT licence, as listed on this page. Check the licence file in the repository if you plan to redistribute or modify it.
Does this skill count tokens accurately?
No. The bundled script uses a rough character-ratio estimate and is labelled demo-only. Use a proper tokenizer if you need precise token counts.
What is the difference between context-fundamentals and context-optimization?
context-fundamentals explains the concepts, such as what context is and how attention works. context-optimization handles the operational work of reducing token cost through tactics like masking, partitioning, prefix caching and budgets.
Why won't the agent fix my lost-in-the-middle problem with this skill?
The skill says debugging attention failures belongs to context-degradation. Use that skill for diagnosis, since this one only explains the underlying mechanics.
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Our verdict
Use this skill if you are new to building LLM agents, onboarding contributors, or need a grounded explanation of how attention limits agent behaviour before you touch prompts. Pick a different skill if you need hands-on debugging, token cost reduction, summarization or project design, since those belong to the specialized skills it routes to.
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