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Knowhere

作者 Ontos AI · GitHub ↗ · v0.1.0-beta.0 · MIT-0
cross-platform ✓ 安全检测通过
200
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0
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2
当前安装
1
版本数
在 OpenClaw 中安装
/install clawhub-knowhere
功能描述
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.
使用说明 (SKILL.md)

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"
}
安全使用建议
This skill itself is just documentation for using the external Knowhere OpenClaw plugin and requests nothing unexpected. Before enabling or using it: (1) install and review the referenced plugin (@ontos-ai/knowhere-claw) from its GitHub repo to confirm you trust its behavior (look for network calls, external uploads, or use of credentials); (2) confirm you are comfortable enabling plugins.entries.knowhere.enabled in your OpenClaw config; (3) be aware agents may call the knowhere tools autonomously (disable model-invocation or restrict the skill if you don't want automatic access); and (4) when attaching files, note the skill expects absolute file paths—ensure the agent has only the file-system access you intend. If you cannot review the plugin code, test in an isolated environment first.
功能分析
Type: OpenClaw Skill Name: clawhub-knowhere Version: 0.1.0-beta.0 The skill bundle provides instructions and metadata for the 'knowhere' plugin, which facilitates document ingestion, search, and management within OpenClaw. The tools described (e.g., knowhere_ingest_document, knowhere_grep) and the recommended workflows in SKILL.md are consistent with legitimate document processing tasks, and no evidence of malicious intent, data exfiltration, or unauthorized execution was found.
能力评估
Purpose & Capability
Name, description, and runtime instructions consistently describe using the Knowhere OpenClaw plugin (known toolnames like knowhere_ingest_document, knowhere_grep, etc.). The single required config path (plugins.entries.knowhere.enabled) matches the stated prerequisite to enable the plugin.
Instruction Scope
SKILL.md limits runtime actions to calls to knowhere_* tools and guidance on how to pass file paths, URLs, and docIds. It does not instruct the agent to read unrelated system files, environment variables, or to send data to arbitrary endpoints. It does assume the external plugin is installed and enabled.
Install Mechanism
There is no install spec and no code files; the skill is instruction-only. The README and SKILL.md instruct installing the external plugin from a known package name; no archives or third-party download URLs are embedded in the skill itself.
Credentials
The skill declares no environment variables or credentials. The only configuration requirement is enabling the plugin entry (plugins.entries.knowhere.enabled), which is appropriate for a plugin-focused skill.
Persistence & Privilege
The skill does not request always:true and does not modify other skills. Model invocation is enabled (default), which is expected for a tool skill; user-invocable is false (the skill is intended to be used programmatically by agents), which is unusual but not incoherent.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install clawhub-knowhere
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /clawhub-knowhere 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.1.0-beta.0
- Initial beta release of the Knowhere skill for ClawHub. - Provides guidance on ingesting, searching, inspecting, and managing documents using the Knowhere OpenClaw plugin. - Lists tool selection strategies and recommended workflows for document operations. - Includes response style best practices, retrieval rules, and attachment handling instructions. - Offers example payloads for common tool actions.
元数据
Slug clawhub-knowhere
版本 0.1.0-beta.0
许可证 MIT-0
累计安装 2
当前安装数 2
历史版本数 1
常见问题

Knowhere 是什么?

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. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 200 次。

如何安装 Knowhere?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install clawhub-knowhere」即可一键安装,无需额外配置。

Knowhere 是免费的吗?

是的,Knowhere 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Knowhere 支持哪些平台?

Knowhere 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Knowhere?

由 Ontos AI(@erickthoughts)开发并维护,当前版本 v0.1.0-beta.0。

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