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orionbelt-semantic-layer

Skill Data & Analytics Poor

Open-source Semantic Sidecar for AI, analytics, and governed data systems. Compiles declarative YAML models into optimized SQL, semantic context, KPIs, and DQ rules.

58 starsFreeQuick setup
Below standard — Significant caveats apply. Not recommended without careful review of the security and evaluation sections.

Reduces SQL complexity and governance overhead by converting declarative models into production-ready queries, metrics, and data quality rules—lowering maintenance cost and enabling consistent metric definitions across teams.

Analytics engineering teams implementing governed semantic layers for self-service BI and AI systems.

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https://github.com/ralforion/orionbelt-semantic-layer

By ralforion

How to Get It

Option 1: Claude Desktop App (Code Mode)Click the + button next to the prompt box → PluginsAdd plugin. Search and click Install. Skills work in Claude Code only.
Option 2: Paste into Claude CodeCopy the command below and paste it into your conversation. Claude will install it.
Command
claude plugins install ralforion/orionbelt-semantic-layer

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

CostFree

Trust Signals Auto-scanned

Stars58Last updated2026-06-22Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-06-22 · scanner v1

Community Pulse New

No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.

Reviewer notes

Auto-scanned review. These are observations, not a security certification.

Scored from trust signals (evidence-eval-v1): 58 GitHub stars; contributors unknown; last commit 0d ago; license no license.

How to evaluate tools before deploying →

Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.

Evaluation

Ease of Use
1/5
Versatility
3/5
Reliability
3/5
Security
3/5
Overall score2.30 / 5.00 PoorEvaluatedJun 2026
Scored from trust signals (evidence-eval-v1): 58 GitHub stars; contributors unknown; last commit 0d ago; license no license.

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