Context Engineering
CheckedContext Engineering refines AI prompts by strategically adding relevant background info, boosting response accuracy and coherence for complex tasks.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add itsmostafa/llm-engineering-skills --skill context-engineering -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
itsmostafa
Taken from the source listing. We haven't verified who controls this account.
Install target
Live repository
Not pinned. Installing fetches whatever the repository holds at the time you run the command.
Automated safety checks
This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.
Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned itsmostafa/llm-engineering-skills at c364a15d51.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- c364a15d51
- Scanned
- 3 files, 1,001 lines
About this skill
What it does
The itsmostafa-context-engineering skill enables AI agents to structure and manage context effectively for improved reasoning and task completion. It allows you to inject specific information, format data in a structured way (like JSON), and guide the agent's focus by providing relevant background material. This leads to more accurate responses and better adherence to instructions.
When to use it
- Complex Reasoning: When an AI needs to synthesize information from multiple sources or perform multi-step reasoning tasks.
- Data Formatting: To ensure data is presented in a consistent, machine-readable format (e.g., JSON) for further processing.
- Focused Assistance: When you want the agent to concentrate on a specific topic by providing targeted background information.
- Improving Accuracy: When the AI's responses are inaccurate or irrelevant due to insufficient context.
Key capabilities
- Context Injection: Providing relevant data and background information.
- Structured Data Formatting: Organizing data into formats like JSON.
- Focus Guidance: Directing the agent’s attention to specific areas of knowledge.
Example prompts
- "Here's a JSON object describing a customer order:
{...}. Analyze this order and identify potential shipping issues." - "I need you to summarize this article about climate change [article text]. Focus on the economic impact section."
- "Given this document outlining company policy [document text], explain how it applies to employee vacation requests."
Tips & gotchas
The skill's effectiveness depends heavily on the quality and relevance of the context provided. Ensure the information is accurate and directly related to the task at hand for optimal results.