chroma-cloud

Original：🇺🇸 English

Translated

Provides expertise on Chroma Cloud integration for semantic search and hybrid search applications. Use when the user is working with Chroma Cloud, CloudClient, managed collections, Schema(), Search(), hybrid search, or Chroma Cloud CLI workflows.

6installs

Sourcechroma-core/agent-skills

Added on2026-05-27

NPX Install

npx skill4agent add chroma-core/agent-skills chroma-cloud

SKILL.md Content

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Instructions

Intake

Do not block on a long questionnaire. Ask only for details that are missing and required to choose the right path:

Dense only or hybrid search

Whether

CHROMA_API_KEY

,

CHROMA_TENANT

, and

CHROMA_DATABASE

are already configured

Existing embedding choice, if any

If the user has no embedding preference, default to Chroma Cloud Qwen. If hybrid search is required, use

Schema()

and

Search()

. If the task is narrow, such as fixing an existing query, reviewing code, or answering an API question, proceed with the repo context instead of forcing intake.

What to validate

Correct client import (
```
CloudClient
```
vs
```
Client
```
)
Environment variables are set for Cloud deployments
Embedding function package is installed when the selected TypeScript embedding requires one
```
Schema()
```
and
```
Search()
```
are only used for Cloud workflows
Important:
```
get_or_create_collection()
```
accepts either an
```
embedding_function
```
OR a
```
schema
```
, but not both. Use
```
schema
```
when you need multiple indexes, hybrid search, or sparse embeddings; use
```
embedding_function
```
for simple dense-only search.

Quick Start

Use the CLI topic to authenticate and write Cloud credentials:

bash

chroma login
chroma db create <db_name>
chroma db connect <db_name> --env-file

Then create a

CloudClient

and choose the API based on the search mode:

typescript

import { CloudClient } from 'chromadb';

const client = new CloudClient();
const collection = await client.getOrCreateCollection({ name: 'my_collection' });

Use

collection.query()

for dense-only search. Use

Schema()

plus

Search()

only when the user needs hybrid retrieval, multiple indexes, or more expressive ranking/query composition.

Cloud Guidance

Collections are the main isolation boundary in Chroma Cloud, and metadata is the main filtering mechanism inside a collection. Reach for

Schema()

only when you need explicit dense+sparse or multi-index configuration, and reach for

Search()

only when

query()

is not expressive enough.

Learn More

If you need more detailed information about Chroma beyond what's covered in this skill, fetch Chroma's llms.txt for comprehensive documentation: https://docs.trychroma.com/llms.txt

Available Topics

Typescript

Chroma Regex Filtering - Learn how to use regex filters in Chroma queries
Query and Get - Query and Get Data from Chroma Collections
Metadata - Store and query metadata, including filters and array values
Updating and Deleting - Update existing documents and delete data from collections
Schema - Schema() configures collections with multiple indexes
Chroma Cloud Qwen - Chroma's hosted Qwen embedding service
Error Handling - Handling errors and failures when working with Chroma
Collection Forking - Instantly duplicate collections using copy-on-write forking in Chroma Cloud
Search() API - An expressive and flexible API for doing dense and sparse vector search on collections, as well as hybrid search

Python

Chroma Regex Filtering - Learn how to use regex filters in Chroma queries
Query and Get - Query and Get Data from Chroma Collections
Metadata - Store and query metadata, including filters and array values
Updating and Deleting - Update existing documents and delete data from collections
Schema - Schema() configures collections with multiple indexes
Chroma Cloud Qwen - Chroma's hosted Qwen embedding service
Error Handling - Handling errors and failures when working with Chroma
Collection Forking - Instantly duplicate collections using copy-on-write forking in Chroma Cloud
Search() API - An expressive and flexible API for doing dense and sparse vector search on collections, as well as hybrid search

General

Data Model - An overview of how Chroma stores data
Integrating Chroma into an existing system - Guidance for adding Chroma search to an existing application
Chroma CLI - Getting started with the Chroma CLI for Chroma Cloud authentication and database management
Caching Collection References - Reduce repeated collection lookup requests in high-traffic Chroma Cloud applications
Quotas and Limits - Chroma Cloud quotas and request limits