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clawhub-knowhereClawHub knowhere 搜索

Agent Skill

clawhub-knowhere 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。

总安装

5,940

周安装

250

GitHub Stars

公开资料未说明

下载量

2,080
OpenClaw

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

MIT-0

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:clawhub-knowhere(ClawHub knowhere 搜索)
来源仓库:https://github.com/erickthoughts/clawhub-knowhere
安装命令:
openclaw skills install clawhub-knowhere
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 clawhub-knowhere

简介

使用 Knowhere OpenClaw 插件提取本地文件或 URL、搜索存储的文档、检查解析的结果、检查作业并清理存储的文档状态。

SKILL.md

name
knowhere
description
Use the Knowhere OpenClaw plugin to ingest local files or URLs, search stored documents, inspect parsed results, check jobs, and clean up stored document state.
user-invocable
false
metadata
{"openclaw":{"homepage":"https://github.com/Ontos-AI/knowhere-openclaw-plugin","requires":{"config":["plugins.entries.knowhere.enabled"]}}}

Knowhere Skill

This ClawHub skill depends on the Knowhere OpenClaw plugin and teaches agents how to use the knowhere_* tools well.

Prerequisite

Install the plugin before using this skill:

openclaw plugins install @ontos-ai/knowhere-claw

Then enable the knowhere plugin entry in OpenClaw and restart OpenClaw.

When to Use Knowhere

Use Knowhere when the user wants to:

  • ingest a local file or URL into the current scope
  • inspect, summarize, or quote previously ingested documents
  • inspect ingest jobs or import a completed Knowhere job
  • preview, list, remove, or clear stored documents
  • understand what fields exist inside the stored result package

Do not assume an uploaded attachment was already ingested. If the user asks you to use an attached file and no existing Knowhere result already covers it, call knowhere_ingest_document.

Tool Selection

  • knowhere_ingest_document for new local files or URLs
  • knowhere_list_documents to find candidate docId values in the current scope
  • knowhere_preview_document for a quick structural overview
  • knowhere_grep for text search across chunk fields
  • knowhere_read_result_file for manifest.json, hierarchy.json, kb.csv, table HTML, or other text-like files under result/
  • knowhere_list_jobs, knowhere_get_job_status, and knowhere_import_completed_job for async jobs
  • knowhere_remove_document and knowhere_clear_scope for cleanup

After ingesting a document, use the returned identifiers for follow-up operations instead of guessing names.

Recommended Workflow

  1. Ingest or import the document if it is not already in the store.
  2. Call knowhere_list_documents if you need to confirm the right docId.
  3. Call knowhere_preview_document to get a structural overview.
  4. Call knowhere_grep with conditions: [{ pattern: "your query" }] for the default text search path.
  5. Narrow by chunk.path, chunk.type, or other conditions when needed.
  6. Call knowhere_read_result_file for manifest.json, hierarchy.json, kb.csv, or table HTML when the answer depends on raw package data.

Response Style

Keep tool-driven replies short and labeled.

  • Reuse labels such as Scope, Source, File, Chunks, Job ID, and Next
  • Prefer one short status line plus the key fields the user needs for the next step
  • Keep path in your reasoning and answers when possible
  • Cite chunkId and path when answering from retrieved chunks

Retrieval Rules

  • Prefer knowhere_grep for text search
  • Use knowhere_preview_document before broad reads when the document is large or the relevant branch is unclear
  • For image or table questions, inspect matching image or table chunks and related manifest asset entries before answering
  • Do not rely on full.md alone when the question depends on exact structure, tables, or images
  • When a tool response contains truncatedStrings: true, retry with a higher maxStringChars before answering

Attachment Markers

When a prompt contains a marker like:

[media attached: /absolute/path/to/file.pdf (application/pdf) | handbook.pdf]

Use:

  • the exact absolute path as filePath
  • the visible filename as fileName

Tool Usage Examples

Ingest a local file:

{
  "filePath": "/tmp/uploads/handbook.pdf",
  "fileName": "handbook.pdf"
}

Ingest a URL:

{
  "url": "https://example.com/report-2026.pdf",
  "title": "Q1 Report"
}

Preview a document:

{
  "docId": "handbook-1234"
}

Search across chunk fields:

{
  "docId": "paper-pdf-a370ef58",
  "conditions": [{ "pattern": "npm audit" }]
}

Read manifest JSON:

{
  "docId": "handbook-1234",
  "filePath": "manifest.json",
  "mode": "json"
}

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

79.44%
按下载量换算1,652

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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