9router-embeddings

9router-embeddings is a RAG & retrieval skill for AI agents, published by decolua in the 9router repository on GitHub. Skillspace rates 9router-embeddings D (68/100) and the safety scan flagged it for review; the rating is based on static analysis only.

Generate vector embeddings via 9Router /v1/embeddings using OpenAI / Gemini / Mistral / Voyage / Nvidia / GitHub embedding models for RAG, semantic search, similarity. Use when the user wants embeddings, vectors, RAG, semantic search, or to embed text.

Grade
D
Quality
68 / 100
Safety
Needs review
GitHub stars
27,026

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.

View source on GitHubdecolua/9router

Our review

Architecture
100 / 100
Maturity
Basic: a single SKILL.md
Security scan
Medium-risk patterns
License
Not declared. Check the repository before reusing it.
Adoption
Adopted by 0 other repositories, in 0 collections
Scope
Vendor-specific: built around one product. Uses the 9Router product's public embeddings API endpoints

What the scanner flagged

  • reads environment variables

Not checked 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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