model-prompting
model-prompting is a Prompt design & optimisation skill for AI agents, published by kyh in the vibedgames repository on GitHub. Skillspace rates model-prompting D (62/100) and it passed the safety scan; the rating is based on static analysis only.
Model-family-specific prompt craft for model endpoints. Trigger when the user mentions a specific model family by name and asks how to prompt it ("how do I prompt Kling", "GPT Image 2 prompt structure", "Happy Horse tips"), or when prompts to a routed endpoint keep coming back generic and the family's known nuances should be applied. For endpoint selection ("which model for X"), use `model-catalog` instead. This skill is about how to talk to a model once it has been chosen.
- Grade
- D
- Quality
- 62 / 100
- Safety
- Passed
- GitHub stars
- 53
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
- 78 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
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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