local-model-onboarding
local-model-onboarding is a Local & open models skill for AI agents, published by sunholo-data in the ailang repository on GitHub. Skillspace rates local-model-onboarding C (76/100) and it passed the safety scan; the rating is based on static analysis only.
Onboard a new on-device model to the Mac Studio eval rig end-to-end — hardware size/shape feasibility gate, OpenRouter quality pre-screen, ollama pull, opencode+pi cross-harness registration in models.yml, and continuous-rotation wiring. Use when the user wants to add/test/try a new local (Ollama) model on the rig, asks whether a model is the right size/shape for the hardware, or wants to evaluate a candidate before committing rig time.
- Grade
- C
- Quality
- 76 / 100
- Safety
- Passed
- GitHub stars
- 33
Unproven: rated by static analysis only, not yet compared head-to-head.
Not launch-quality. It is graded C with a clean safety verdict, but our quality filters exclude it: a model that read it found it written only for the repository it lives in. So it is not in our launch-quality set, the skills our MCP server searches and recommends. How launch-quality is decided
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 99 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- Low-risk patterns
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
- Scope
- Repo-internal: written for the repository it lives in. Onboards models onto their specific Mac Studio rig and models.yml
What the scanner flagged
- mentions secrets in text
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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