bonsai
bonsai is a System design & architecture decisions skill for AI agents, published by NehmeAILabs in the bonsai repository on GitHub. Skillspace rates bonsai B (80/100) and it passed the safety scan; the rating is based on static analysis only.
The art of keeping your AI stack small and shaped on purpose. Use when building AI features, selecting models, designing extraction/RAG/agent pipelines, or about to reach for a frontier LLM (GPT-5, Claude Opus, Gemini Pro). Enforces a smallest-tool-first ladder (regex, spaCy NER, small LLM, frontier) and challenges JSON-everywhere, RAG-everywhere, browser-automation-everywhere defaults. Use whenever the user mentions token cost, latency, model sizing, structured output, RAG, or agent architecture.
- Grade
- B
- Quality
- 80 / 100
- Safety
- Passed
- GitHub stars
- 51
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 94 / 100
- Maturity
- Packaged: licensed, with a version or references
- 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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