context-engineering
context-engineering is a Prompt design & optimisation skill for AI agents, published by sirkirby in the unifi-network-rules repository on GitHub. Skillspace rates context-engineering D (62/100) and it passed the safety scan; the rating is based on static analysis only.
Design effective prompts and optimize context for AI models and agents. Covers prompt engineering foundations (clarity, examples, chain of thought, XML structure), the four context engineering strategies (Write, Select, Compress, Isolate), agent memory and session patterns, and before/after examples showing measurable improvement. Use when writing system prompts, designing agent workflows, optimizing context windows, building prompt templates, structuring few-shot examples, reducing context rot, or improving AI output quality.
- Grade
- D
- Quality
- 62 / 100
- Safety
- Passed
- GitHub stars
- 59
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 84 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- Low-risk patterns
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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