OpenClaw

orchata-rag

Knowledge management and RAG platform with tree-based document indexing. Use this skill to search, browse, and manage Orchata knowledge bases via MCP tools.

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查看来源 ↗安装与使用 SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install ehudsn/orchata

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

Orchata Skills

This document describes how to effectively use Orchata, a RAG (Retrieval-Augmented Generation) platform with tree-based document indexing. Load this into your context to interact with Orchata knowledge bases.

What is Orchata?

Orchata is a knowledge management platform that:

Organizes documents into Spaces - Logical containers for related content
Uses tree-based indexing - Documents are parsed into hierarchical structures with sections, summaries, and page ranges
Provides semantic search - Find relevant content using natural language queries
Exposes MCP tools - AI assistants can directly manage and query knowledge bases

Core Concepts

Spaces

A Space is a container for related documents. Think of it as a folder with semantic search capabilities.

Each space has a name, description, and optional icon
Descriptions are used by smart_query to recommend relevant spaces
Spaces can be archived (soft-deleted)

Documents

A Document is content within a space. Supported formats include:

PDF (text-based and scanned with OCR)
Word documents (.docx)
Excel spreadsheets (.xlsx)
PowerPoint presentations (.pptx)
Markdown files (.md)
Plain text files (.txt)
Images (PNG, JPG, etc.)

Document Status:

Status	Description
`PENDING`	Uploaded, waiting for processing
`PROCESSING`	Being parsed and indexed
`COMPLETED`	Ready for queries
`FAILED`	Processing error occurred

Important: Only query documents with status: "COMPLETED". Other statuses won't return results.

Document Trees

Documents are indexed into hierarchical tree structures:

Each tree has nodes representing sections/chapters
Nodes contain: title, summary, startPage, endPage, textContent
Trees enable precise navigation of large documents

Queries

Two types of queries are available:

query_spaces - Search document content using tree-bas...

来源信息

Source: github
Repository: openclaw/skills
Path: skills/ehudsn/orchata
Version: —
Commit: f03a4f862c392f10b7ded2eceb756d9720a7edce
分类来源: rules
状态: active
可见性: public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md

# Orchata Skills

This document describes how to effectively use Orchata, a RAG (Retrieval-Augmented Generation) platform with tree-based document indexing. Load this into your context to interact with Orchata knowledge bases.

## What is Orchata?

Orchata is a knowledge management platform that:

- **Organizes documents into Spaces** - Logical containers for related content
- **Uses tree-based indexing** - Documents are parsed into hierarchical structures with sections, summaries, and page ranges
- **Provides semantic search** - Find relevant content using natural language queries
- **Exposes MCP tools** - AI assistants can directly manage and query knowledge bases

## Core Concepts

### Spaces

A **Space** is a container for related documents. Think of it as a folder with semantic search capabilities.

- Each space has a `name`, `description`, and optional `icon`
- Descriptions are used by `smart_query` to recommend relevant spaces
- Spaces can be archived (soft-deleted)

### Documents

A **Document** is content within a space. Supported formats include:

- PDF (text-based and scanned with OCR)
- Word documents (.docx)
- Excel spreadsheets (.xlsx)
- PowerPoint presentations (.pptx)
- Markdown files (.md)
- Plain text files (.txt)
- Images (PNG, JPG, etc.)

**Document Status:**

| Status | Description |
| ------ | ----------- |
| `PENDING` | Uploaded, waiting for processing |
| `PROCESSING` | Being parsed and indexed |
| `COMPLETED` | Ready for queries |
| `FAILED` | Processing error occurred |

**Important:** Only query documents with `status: "COMPLETED"`. Other statuses won't return results.

### Document Trees

Documents are indexed into **hierarchical tree structures**:

- Each tree has nodes representing sections/chapters
- Nodes contain: `title`, `summary`, `startPage`, `endPage`, `textContent`
- Trees enable precise navigation of large documents

### Queries

Two types of queries are available:

1. **`query_spaces`** - Search document content using tree-bas...

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