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Agent Skill · 研究检索

personal-kb-lite(个人知识库精简版)

personal-kb-lite 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。

personal-kb-lite 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;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 18,266。

总安装 6,169周安装 252GitHub Stars 1下载 1,976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:personal-kb-lite(个人知识库精简版)
来源仓库:https://github.com/congshengwu/personal-kb-lite
安装命令:
openclaw skills install personal-kb-lite
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 personal-kb-lite

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。

个人知识库精简版扫描本地文档并构建可搜索的知识索引。适用于管理 .txt、.md、.pdf 等多种格式的私有资料库。利用法学硕士模型实现语义问答与元数据提取。安装命令为 openclaw skills install personal-kb-lite,需指定文档目录路径。

使用前建议检查是否占用过多磁盘空间或影响系统性能。

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 personal-kb-lite;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

    它需要接触敏感数据,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

personal-kb-lite 怎么安装?

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

personal-kb-lite 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。

personal-kb-lite 需要什么权限?

权限级别是接触敏感数据。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。

personal-kb-lite 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。

personal-kb-lite 用的人多吗?

公开数据是累计安装 6,169 次,近一周安装 252 次,下载 1,976 次,GitHub 1 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。

personal-kb-lite 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

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
personal-kb-lite

个人知识库精简版 · 本页

6,1691接触敏感数据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
personal-kb-lite
description
>
version
1.0.0
metadata
openclaw
requires
bins
install
package
pdfplumber
package
python-docx
package
openpyxl
keywords
categories
command
kb
emoji
📚

Task: Local Knowledge Base

Arguments: $ARGUMENTS

Mode Selection

  • If $ARGUMENTS is --alias <name>: set a custom command alias — save {"command_alias": "<name>"} into .kb-config.json (merge with existing fields), then reply: Command alias set to /<name>. Terminate.
  • If $ARGUMENTS is --alias reset: remove the command_alias field from .kb-config.json, then reply: Command alias reset to default /kb. Terminate.
  • If $ARGUMENTS is empty (user only typed /kb), execute the Indexing Workflow below
  • If $ARGUMENTS is not empty, treat it as a user question and execute the Q&A Workflow below

Indexing Workflow

Step 1: Confirm Watch Directory

  1. Read .kb-config.json from the current working directory using the Read tool
  2. If the file exists and watch_dir is a non-empty string, use it as WATCH_DIR
  3. If the file does not exist or watch_dir is empty, ask the user:

> Please enter the absolute path of the directory to watch:

Save the user's input as WATCH_DIR, and write the following to .kb-config.json using the Write tool:

   {"watch_dir": "<WATCH_DIR>"}
  1. Verify the directory exists using Bash:
   ls "<WATCH_DIR>" > /dev/null 2>&1 && echo "ok" || echo "not_found"

If it returns not_found, inform the user and terminate.

Step 2: Load Existing Metadata

Read <WATCH_DIR>/.kb-meta.json using the Read tool.

  • If the file exists, parse the JSON and extract the files object (keyed by filename)
  • If it does not exist, initialize files = {}

Step 3: Scan Directory for New and Modified Files

List files recursively in the directory using Bash:

find "<WATCH_DIR>" -type f \( -name "*.txt" -o -name "*.md" -o -name "*.docx" -o -name "*.pdf" -o -name "*.xlsx" -o -name "*.csv" \) -not -name ".kb-meta.json" -print

For each file found, get its modification time using Bash:

stat -f "%m" "<filepath>"   # macOS
stat -c "%Y" "<filepath>"   # Linux

A file needs (re-)indexing if:

  • Its relative path is not in the files object, OR
  • Its modification time is newer than the indexed_at timestamp in the existing entry

Also, remove any entries from files whose files no longer exist on disk (stale cleanup).

Use the relative path from WATCH_DIR as the key (e.g., subdir/report.pdf).

If there are no files to process and no stale entries to clean, output:

No changes detected (X files already indexed)

Then terminate.

Step 4: Process Each File That Needs Indexing

For each file, follow these steps:

4a. Read File Content

Read the file using the method described in Appendix: File Reading Methods below, with MAX_CHARS = 8000.

If reading fails, record "error": "Read failed: <error message>" in the file's metadata entry and skip to the next file.

4b. Extract Metadata

After reading the file content, generate the following fields:

  • summary: A 100-200 word summary describing the file's core content and purpose
  • tags: 3-8 classification tags as a JSON array
  • toc: A list of the file's major section/chapter titles as a JSON array (max 20 items); return an empty array if no clear structure exists
4c. Update and Save Metadata Immediately

Add the following entry to the files object:

"<filename>": {
  "filename": "<filename>",
  "summary": "<summary>",
  "tags": ["tag1", "tag2"],
  "toc": ["section1", "section2"],
  "indexed_at": "<current time, ISO 8601 format>",
  "file_size": <bytes, obtained via Bash wc -c>
}

Write the complete .kb-meta.json back to disk immediately after processing each file, to avoid losing progress if interrupted.

Show progress for each file, e.g.:

[1/3] Processing: contract_template.txt ... done
[2/3] Processing: product_manual.pdf ... done
[3/3] Processing: quotation.xlsx ... failed (read error)

Step 5: Output Summary

Indexing complete
  Total files scanned: X
  Newly indexed: Y
  Failed/skipped: Z
  Metadata file: <WATCH_DIR>/.kb-meta.json

Q&A Workflow

User question: $ARGUMENTS

Step 1: Load Configuration and Metadata

  1. Read .kb-config.json from the current working directory using the Read tool, and get the watch_dir field (referred to as WATCH_DIR)

If the file does not exist or watch_dir is empty, reply: > Knowledge base directory not configured. Please run /kb first to set up the index.

Then terminate.

  1. Read <WATCH_DIR>/.kb-meta.json using the Read tool

If the file does not exist or files is an empty object, reply: > Knowledge base index is empty. Please run /kb first to build the index.

Then terminate.

Step 2: Build File Index Summary

Organize each entry in files into a single line of plain text:

File: contract_template.txt, Summary: Standard procurement contract template with rights and obligations..., Tags: contract, procurement, template, TOC: Article 1 Definitions, Article 2 Rights, Article 3 Breach
File: product_manual.pdf, Summary: Technical specifications and installation guide for Product A..., Tags: product, specs, TOC: Overview, Installation, FAQ
  • If a field is empty or missing, omit it
  • toc: show at most the first 15 items, comma-separated
  • tags: comma-separated

Step 3: Identify Relevant Files

Based on the index summary and user question, determine which files may contain the answer.

Criteria:

  • The file's summary, tags, or table of contents contain information semantically related to the question
  • Prefer including a marginally relevant file over missing a potentially useful one

If no files are possibly relevant, reply directly:

Sorry, no files related to your question were found in the knowledge base. Current indexed file count: X Suggestion: Verify the question falls within the knowledge base scope, or run /kb to update the index.

Then terminate.

Record the matched filenames as an internal variable MATCHED_FILES (do not show this list to the user).

Step 4: Read Full Content of Relevant Files

For each filename in MATCHED_FILES, read the file using the method described in Appendix: File Reading Methods below (no truncation, omit MAX_CHARS).

If a file fails to read, skip it and continue with the remaining files.

Step 5: Generate Answer

Based on the content of the retrieved files, answer the user's question.

Requirements:

  1. Answer directly, preferring to quote the file's original text, data, or specific statements
  2. If multiple files contain relevant information, synthesize the answer and note which file each part comes from
  3. If the file content can only partially answer the question, indicate which parts could not be found in the knowledge base
  4. Append citation sources at the end of the answer, formatted as:
---
Sources:
[1] contract_template.txt
[2] product_manual.pdf

Only list files actually used in the answer; do not include matched but unused files.


Appendix: File Reading Methods

Use the following methods based on file extension. All Bash commands pass the file path via the KB_FILE environment variable to avoid filename injection issues.

Optional parameter MAX_CHARS: if provided, truncate output to that many characters; if omitted, output the full content.

  • .txt / .md / .csv: Read using the Read tool at <WATCH_DIR>/<filename>. If MAX_CHARS is set, only read the first MAX_CHARS characters (approximately MAX_CHARS / 40 lines).
  • .docx: Run via Bash:
  KB_FILE="<WATCH_DIR>/<filename>" python3 -c "
  import docx, os
  doc = docx.Document(os.environ['KB_FILE'])
  text = '\
'.join(p.text for p in doc.paragraphs if p.text.strip())
  limit = int(os.environ.get('KB_MAX_CHARS', '0'))
  print(text[:limit] if limit else text)
  "
  • .pdf: Run via Bash:
  KB_FILE="<WATCH_DIR>/<filename>" python3 -c "
  import pdfplumber, os
  with pdfplumber.open(os.environ['KB_FILE']) as pdf:
      text = '\
'.join(p.extract_text() or '' for p in pdf.pages)
  limit = int(os.environ.get('KB_MAX_CHARS', '0'))
  print(text[:limit] if limit else text)
  "
  • .xlsx: Run via Bash:
  KB_FILE="<WATCH_DIR>/<filename>" python3 -c "
  import openpyxl, os
  wb = openpyxl.load_workbook(os.environ['KB_FILE'], data_only=True)
  rows = []
  for ws in wb.worksheets:
      for row in ws.iter_rows(values_only=True):
          line = '\	'.join(str(v) for v in row if v is not None)
          if line.strip():
              rows.append(line)
  text = '\
'.join(rows)
  limit = int(os.environ.get('KB_MAX_CHARS', '0'))
  print(text[:limit] if limit else text)
  "

When MAX_CHARS is needed, prepend KB_MAX_CHARS="<value>" to the environment variables, e.g.:

KB_FILE="..." KB_MAX_CHARS="8000" python3 -c "..."

平台分布

OpenClaw

79.58%
按下载量换算1,573

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

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。目前只有一个公开来源,建议同时核对源仓库。

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