vector
vector is a RAG & retrieval skill for AI agents, published by SEMOSS in the Semoss repository on GitHub. Skillspace rates vector D (62/100) and it passed the safety scan; the rating is based on static analysis only.
Use when writing code in an app that does semantic search, RAG, or ingests documents into a vector database on the platform — running nearest-neighbor queries, listing/adding/removing documents, or feeding retrieved chunks into an LLM. Covers VectorDatabaseQuery(), ListDocumentsInVectorDatabase(), CreateEmbeddingsFromDocuments(), CreateEmbeddingsFromVectorCSVFile(), and RemoveDocumentFromVectorDatabase() pixel commands via @semoss/sdk's runPixel, plus listing engines with MyEngines(engineTypes=["VECTOR"]). Do not use for raw SQL/graph queries (see database-engine) or direct LLM calls without retrieval (see model-engine).
- 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
- 96 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Low-risk patterns
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
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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