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Agent Skill · 研究检索

orchata(orchata 文档)

orchata 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

orchata 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为调用外部服务;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 5,722。

总安装 24,628周安装 1,016GitHub Stars 2下载 8,047核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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:orchata(orchata 文档)
来源仓库:https://github.com/ehudsn/orchata
安装命令:
openclaw skills install orchata
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install orchata

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

具有基于树的文档索引的知识管理和 RAG 平台。使用此技能通过 MCP 工具搜索、浏览和管理 Orchata 知识库。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install orchata;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

orchata 怎么安装?

在终端执行 openclaw skills install orchata。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

orchata 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

orchata 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

orchata 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

orchata 用的人多吗?

公开数据是累计安装 24,628 次,近一周安装 1,016 次,下载 8,047 次,GitHub 2 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

orchata 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
orchata

orchata 文档 · 本页

24,6282调用外部服务MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
orchata-rag
description
Knowledge management and RAG platform with tree-based document indexing. Use this skill to search, browse, and manage Orchata knowledge bases via MCP tools.
metadata
version
1.0.0
author
Orchata AI

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:

StatusDescription
PENDINGUploaded, waiting for processing
PROCESSINGBeing parsed and indexed
COMPLETEDReady for queries
FAILEDProcessing 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-based reasoning
  2. smart_query - Discover which spaces are relevant for a query

MCP Tools Reference

Space Management

list_spaces

List all knowledge spaces in the organization.

list_spaces
list_spaces with status="active"
list_spaces with page=1 pageSize=20

Parameters:

  • page (number, optional): Page number (default: 1)
  • pageSize (number, optional): Items per page (default: 10)
  • status (string, optional): Filter by active, archived, or all

manage_space

Create, get, update, or delete a space.

manage_space with action="create" name="Product Docs" description="Technical documentation"
manage_space with action="create" name="Legal" description="Case files" icon="briefcase"
manage_space with action="get" id="space_abc123"
manage_space with action="update" id="space_abc123" description="Updated description"
manage_space with action="delete" id="space_abc123"

Parameters:

  • action (string, required): create, get, update, or delete
  • id (string): Space ID (required for get/update/delete)
  • name (string): Space name (required for create)
  • description (string, optional): Space description
  • icon (string, optional): Icon name. Defaults to "folder"
  • slug (string, optional): URL-friendly identifier
  • isArchived (boolean, optional): Archive status (for update)

Valid Icons: folder, book, file-text, database, package, archive, briefcase, inbox, layers, box

If an invalid icon is provided, the tool returns an error with the list of valid options.


Document Management

list_documents

List documents in a space.

list_documents with spaceId="space_abc123"
list_documents with spaceId="space_abc123" status="completed"
list_documents with spaceId="space_abc123" status="all"

Parameters:

  • spaceId (string, required): Space ID
  • page (number, optional): Page number
  • pageSize (number, optional): Items per page (max: 100)
  • status (string, optional): Filter by status. Values: pending, processing, completed, failed, or all. Omitting returns all documents.

Note: Status values are case-insensitive (completed and COMPLETED both work).


save_document

Upload or upsert documents (single or batch).

Single document:

save_document with spaceId="space_abc123" filename="guide.md" content="# Guide\
\
Content here..."

Batch upload:

save_document with spaceId="space_abc123" documents=[{"filename": "doc1.md", "content": "..."}, {"filename": "doc2.md", "content": "..."}]

Parameters:

  • spaceId (string, required): Space ID
  • filename (string): Filename (required for single)
  • content (string): Content (required for single)
  • documents (array, optional): Array of {filename, content, metadata} for batch
  • metadata (object, optional): Custom key-value pairs

get_document

Get document content by ID or filename. Returns processed markdown text.

get_document with spaceId="space_abc123" id="doc_xyz789"
get_document with spaceId="space_abc123" filename="guide.md"
get_document with spaceId="*" filename="guide.md"

Parameters:

  • spaceId (string, required): Space ID, or * to search all spaces (requires filename)
  • id (string, optional): Document ID
  • filename (string, optional): Filename

Notes:

  • Either id or filename is required
  • Use spaceId="*" to search all spaces when you know the filename but not the space
  • For completed documents, returns the extracted markdown text (not raw PDF binary)
  • When using *, the response includes the spaceId where the document was found

update_document

Update document content or metadata.

update_document with spaceId="space_abc123" id="doc_xyz789" content="New content..."
update_document with spaceId="space_abc123" id="doc_xyz789" append=true content="Additional content"

Parameters:

  • spaceId (string, required): Space ID
  • id (string, required): Document ID
  • content (string, optional): New content
  • metadata (object, optional): New metadata
  • append (boolean, optional): Append instead of replace
  • separator (string, optional): Separator for append mode

delete_document

Permanently delete a document.

delete_document with spaceId="space_abc123" id="doc_xyz789"

Parameters:

  • spaceId (string, required): Space ID
  • id (string, required): Document ID

Query Tools

query_spaces

Search documents across one or more spaces using tree-based reasoning.

query_spaces with query="How do I authenticate API requests?"
query_spaces with query="installation guide" spaceIds="space_abc123"
query_spaces with query="error handling" spaceIds=["space_abc", "space_def"] topK=10

Parameters:

  • query (string, required): Natural language search query
  • spaceIds (string or array, optional): Space ID(s) to search. Omit or use * for all spaces
  • topK (number, optional): Maximum results (default: 10)
  • compact (boolean, optional): Use compact format (default: false). See When to Use Compact below.

When to Use Compact:

ModeWhen to useWhat you get
compact=false (default)Most queries. Any time you need actual data, facts, numbers, dates, or details from documents.Full results with document metadata, tree context, page ranges, and complete content.
compact=trueBroad discovery queries where you only need to know *which* documents are relevant, not their content.Minimal results: just content snippet, source filename, and score.

Rule of thumb: Default to compact=false. Only use compact=true when you're browsing/surveying and don't need the actual content yet.

Response (compact=true format):

{
  "results": [
    {
      "content": "Relevant text content...",
      "source": "filename.pdf",
      "score": 0.95
    }
  ],
  "total": 5
}

smart_query

Discover which spaces are relevant for a query using LLM reasoning.

smart_query with query="How do I install the SDK?"
smart_query with query="billing questions" maxSpaces=3

Parameters:

  • query (string, required): Query to find relevant spaces for
  • maxSpaces (number, optional): Maximum spaces to return (default: 5)

Response:

{
  "query": "How do I install the SDK?",
  "relevantSpaces": [
    {"spaceId": "space_abc123", "relevance": "Contains SDK installation guides"},
    {"spaceId": "space_def456", "relevance": "Has developer tutorials"}
  ],
  "totalFound": 2
}

Use case: When you don't know which space to search, use smart_query first to discover relevant spaces, then use query_spaces with those space IDs.


Tree Visibility Tools

These tools let you explore the hierarchical structure of indexed documents.

get_document_tree

Get the tree structure of a document showing sections, summaries, and page ranges.

get_document_tree with spaceId="space_abc123" documentId="doc_xyz789"

Parameters:

  • spaceId (string, required): Space ID
  • documentId (string, required): Document ID

Response:

{
  "documentId": "doc_xyz789",
  "totalPages": 45,
  "totalNodes": 12,
  "nodes": [
    {
      "nodeId": "0001",
      "title": "Introduction",
      "summary": "Overview of the system architecture...",
      "pages": "1-5",
      "depth": 0
    },
    {
      "nodeId": "0002",
      "title": "Installation",
      "summary": "Step-by-step installation guide...",
      "pages": "6-12",
      "depth": 0
    }
  ]
}

Use case: Use this to understand a document's structure before drilling into specific sections.


get_tree_node

Get the full text content of a specific tree node/section.

get_tree_node with documentId="doc_xyz789" nodeId="0002"

Parameters:

  • documentId (string, required): Document ID
  • nodeId (string, required): Node ID from the tree structure

Response:

{
  "documentId": "doc_xyz789",
  "filename": "manual.pdf",
  "nodeId": "0002",
  "title": "Installation",
  "summary": "Step-by-step installation guide...",
  "pages": "6-12",
  "depth": 0,
  "content": "## Installation\
\
To install the software, follow these steps:\
\
1. Download the installer...\
\
..."
}

Use case: After viewing the tree structure, use this to read the full content of a specific section.


Workflow Patterns

Pattern 1: Search for Information (Default Approach)

For most questions, a single query_spaces call is all you need. Start here before trying multi-step workflows.

query_spaces with query="your question"

This searches all spaces with full details (compact=false by default). One call, done.

If you want to narrow to specific spaces:

query_spaces with query="your question" spaceIds="known_space_id"

If you truly don't know which spaces exist:

smart_query with query="your question"
# Then use the returned spaceIds:
query_spaces with query="your question" spaceIds=["returned_space_id"]
Avoid over-searching. The multi-step workflow (smart_query -> query_spaces -> get_document_tree -> get_tree_node) is rarely necessary. For most questions, a single query_spaces call returns the answer directly. Only escalate to tree browsing if results are insufficient.

Pattern 2: Look Up Specific Data

When looking for specific facts, numbers, dates, names, or details:

Just query directly -- one call:

query_spaces with query="total amount on invoice #1234"

The default compact=false returns full content with document metadata, so you get the actual data you need in one step. Do not use compact=true for data lookups -- it strips the detail you need.

Pattern 3: Browse a Large Document

When you need to navigate a large document's structure:

  1. Get the document structure:
   get_document_tree with spaceId="space_id" documentId="doc_id"
  1. Identify relevant sections from the node titles and summaries
  1. Read specific sections:
   get_tree_node with documentId="doc_id" nodeId="relevant_node_id"

Pattern 4: Add New Content

When adding documents to a knowledge base:

  1. Find or create the appropriate space:
   list_spaces
   # or
   manage_space with action="create" name="New Space" description="..."
  1. Upload the content:
   save_document with spaceId="space_id" filename="document.md" content="..."
  1. Wait for processing (status will change from PENDING -> PROCESSING -> COMPLETED)
  1. Verify it's ready:
   list_documents with spaceId="space_id" status="COMPLETED"

manage_space - Valid Icons

When creating or updating a space, use one of these icon values:

  • folder (default)
  • book
  • file-text
  • database
  • package
  • archive
  • briefcase
  • inbox
  • layers
  • box

Invalid icons will return a helpful error message with the list of valid options.


list_documents - Status Parameter

The status parameter accepts the following values (case-insensitive):

  • "all" - Returns documents in any status (COMPLETED, FAILED, PENDING, PROCESSING)
  • "completed" - Returns only successfully processed documents
  • "failed" - Returns only documents that failed processing (includes errorMessage field)
  • "pending" - Returns documents waiting to be processed
  • "processing" - Returns documents currently being processed

Documents with status="FAILED" will include an errorMessage field explaining what went wrong during processing.


save_document - Processing Workflow

Documents are processed asynchronously:

  1. save_document returns immediately with status="PROCESSING"
  2. Background job generates embeddings and indexes the document (typically 1-3 seconds)
  3. Status changes to "COMPLETED" when ready
  4. Document becomes searchable via query_spaces

To check completion status:

  • Use get_document to check a specific document's status
  • Use list_documents with status="processing" to see all processing documents
  • Use list_documents with status="failed" to see any failures

Example:

// Save document
const result = await save_document({...});
// result.document.status === "PROCESSING"

// Check status after a moment
const doc = await get_document({id: result.document.id});
// doc.status === "COMPLETED" (when ready)

get_tree_node - Content Availability

get_tree_node may return "(No text content cached for this node)" for certain nodes. This occurs for:

  • Structural/organizational nodes without associated text content
  • Nodes that serve as section headers in the tree hierarchy

This is expected behavior.

To read actual document content:

  • Use get_document to retrieve the full processed markdown
  • Use query_spaces to search and retrieve relevant content chunks

The tree structure (via get_document_tree) is always available and shows document organization, summaries, and page ranges.


Best Practices

DO

  • Start with a single query_spaces call - it usually has the answer in one step
  • Use compact=false (the default) for most queries - you get full content and context
  • Check document status before querying - only COMPLETED documents are searchable
  • Use descriptive queries - natural language works best
  • Use tree tools for large documents - navigate structure instead of reading everything
  • Write good space descriptions - they're used by smart_query for discovery

DON'T

  • Don't over-search - avoid multi-step workflows (smart_query -> query_spaces -> get_document_tree -> get_tree_node) when a single query_spaces call suffices
  • Don't use compact=true for data lookups - it strips the content you need; only use it for broad discovery
  • Don't query PENDING/PROCESSING documents - they won't return results
  • Don't use very short queries - more context = better results
  • Don't forget to check processing status after uploading new documents

Error Handling

Common errors and solutions:

ErrorCauseSolution
"Document not found"Wrong ID or no accessVerify the document ID with list_documents
"Space not found"Wrong ID or archivedUse list_spaces to find valid space IDs
Empty search resultsDocument not COMPLETED or no matchesCheck document status; try broader query
"Tree not found"Document uses vector indexing or not processedCheck if document status is COMPLETED
"Invalid icon"Icon name not in allowed listUse one of: folder, book, file-text, database, package, archive, briefcase, inbox, layers, box
"No text content cached"Tree node content not cachedThis is normal for structural nodes; use get_document for full content

Troubleshooting Tips

If save_document fails:

  1. Verify the space exists with manage_space with action="get" id="..."
  2. Ensure content is valid text/markdown
  3. Check that the space is not archived

If list_documents returns 0 results:

  1. Try status="all" or omit the status parameter entirely
  2. Verify the spaceId is correct with list_spaces
  3. Check if documents are still processing (status="processing")

If get_tree_node returns no content:

  • Some nodes are structural and don't have cached text content
  • Use get_document to get the full processed document text instead
  • Or use query_spaces to search for specific content

Quick Reference

TaskToolExample
List all spaceslist_spaceslist_spaces with status="active"
Create a spacemanage_spacemanage_space with action="create" name="Docs"
List documentslist_documentslist_documents with spaceId="..."
Upload contentsave_documentsave_document with spaceId="..." content="..."
Get document textget_documentget_document with spaceId="..." id="..."
Search contentquery_spacesquery_spaces with query="..."
Find relevant spacessmart_querysmart_query with query="..."
View doc structureget_document_treeget_document_tree with spaceId="..." documentId="..."
Read a sectionget_tree_nodeget_tree_node with documentId="..." nodeId="..."

平台分布

OpenClaw

87.51%
按下载量换算7,042

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。目前只有一个公开来源,建议同时核对源仓库。

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