context-fundamentals

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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 summarization goes to context-compression, and project-shape decisions go to project-development.

AI & Automation 18 stars 1 forks Updated today Apache-2.0

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Quality Score: 81/100

Stars 20%
43
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# 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 skills. - Reasoning about a context-related design decision from first principles (what does this constraint mean, why does this trade-off exist) before picking a specific tactic. - Writing or reviewing documentation that needs to ground operational guidance in the underlying mechanics. Do no...

Details

Author
docxology
Repository
docxology/template
Created
11 months ago
Last Updated
today
Language
Python
License
Apache-2.0

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