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chroma Skill

AI Agent SkillCode Search & MemoryPythonOpen source

Embedding database for RAG and semantic search. Published by NousResearch in hermes-agent.

Decision snapshot

Is this a fit?

Best for

Database workflows, Deployment, Research, Includes SKILL.md

Works with

Compatibility not yet detected.

Access

Permission behavior not yet detected.

Setup

Copy skill directory

Project health

21 days ago · MIT license

Considerations

No specific cautions were detected. Review the source and requested permissions before installing.

What is chroma Skill?

Embedding database for RAG and semantic search. Published by NousResearch in hermes-agent. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.

Trust signal
95/100
Maintenance signal
90/100
Adoption signal
100/100

Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.

Key capabilities

  • Includes SKILL.md support
  • Reusable instructions support
  • Database workflows
  • Deployment
  • Research
  • Database workflows use cases
  • Deployment use cases

Declared skill metadata

  • Declared author: Orchestra Research
  • Declared license: MIT
  • Source file: optional-skills/mlops/chroma/SKILL.md

These fields retain source and confidence evidence from the indexed SKILL.md.

Compatibility and setup

Copy skill directory
  • Install or run with Copy skill directory

When to use chroma Skill

  • Use it for database workflows.
  • Use it for deployment.
  • Use it for research.

Built with

PythonCopy skill directory

Editorial notes

Source

  • Creator: NousResearch
  • Repository: NousResearch/hermes-agent
  • Skill file: optional-skills/mlops/chroma/SKILL.md

What it does

Embedding database for RAG and semantic search.

Skill instructions

Chroma - Open-Source Embedding Database The AI-native database for building LLM applications with memory. When to use Chroma Use Chroma when: - Building RAG (retrieval-augmented generation) applications - Need local/self-hosted vector database - Want open-source solution (Apache 2.0) - Prototyping in notebooks - Semantic search over documents - Storing embeddings with metadata Metrics: - 24,300+ GitHub stars - 1,900+ forks - v1.3.3 (stable, weekly releases) - Apache 2.0 license Use alternatives instead: - Pinecone: Managed cloud, auto-scaling - FAISS: Pure similarity search, no metadata - Weaviate: Production ML-native database - Qdrant: High performance, Rust-based Quick start Installation bash Python pip install chromadb JavaScript/TypeScript npm install chromadb @chroma-core/default-embed Basic usage (Python) python import chromadb Create client client = chromadb.Client() Create collection collection = client.createcollection(name="mycollection") Add documents collection.add( docume

Verified compatibility and discovery

Frequently asked questions

What is chroma?

chroma is a open-source AI agent skill with Copy skill directory. Embedding database for RAG and semantic search.

Who is chroma best for?

chroma is best for reusing agent instructions, scripts, and references, database workflows, deployment workflows, research workflows.

How do I install chroma?

Install or run chroma using Copy skill directory. Check chroma for the latest setup command.

Is chroma actively maintained?

chroma may need a closer maintenance check before production use.

Share:

Stars
232,138
Forks
46,253
Last commit
21 days ago
Last verified
Aug 18, 2026
Metadata fetched
Aug 18, 2026
Repository age
1 year
License
MIT

Project health auto-fetched from the source repository.

Maintain this resource?

Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.

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