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chroma-cloud色度云

Agent Skill

chroma-cloud 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

173

周安装

7

GitHub Stars

15

下载量

54
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:chroma-cloud(色度云)
来源仓库:https://github.com/chroma-core/agent-skills
仓库路径:skills/chroma-cloud
安装命令:
npx skills add https://github.com/chroma-core/agent-skills --skill chroma-cloud
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/chroma-core/agent-skills --skill chroma-cloud

简介

chroma-cloud 用于连接 Chroma Cloud 托管服务,支持密集或混合搜索模式。

  • 需配置 CHROMA_API_KEY、TENANT 和 DATABASE 环境变量建立连接。
  • 可选择 Qwen 或其他嵌入模型,混合搜索模式下结合稀疏与稠密向量提升精度。
  • 适用于生产环境 RAG 应用,无需自行运维基础设施即可获得稳定服务。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

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:

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:

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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.36%
按下载量换算19

Claude

29.11%
按下载量换算16

Cursor

19.01%
按下载量换算10

Gemini CLI

8.67%
按下载量换算5

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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