mcp-engine-model-quality
mcp-engine-model-quality is a Dashboards & data visualisation skill for AI agents, published by maxanatsko in the mcp-engine-public repository on GitHub. Skillspace rates mcp-engine-model-quality C (72/100) and it passed the safety scan; the rating is based on static analysis only.
Assess Power BI semantic models for bad or questionable modeling practices and produce a source-backed quality scorecard. Use when reviewing model quality, semantic model assessment, semantic model best practices, star schema fit, relationships, DAX maintainability, VertiPaq/storage risk, metadata hygiene, governance signals, validation gaps, or when the user asks for a scorecard, recommendations, model audit, model quality review, bad practices review, best practices audit, or best practices assessment.
- Grade
- C
- Quality
- 72 / 100
- Safety
- Passed
- GitHub stars
- 252
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
- 96 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- 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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