據 AlphaMoat 統計,截至 2026-09,文件內容總結 Summary & Analysis txt/docx/pdf/xlsx/xls 累計下載 3,261 次、獲 1 個星標,在全部 5,078 個 AI 技能中排名第 3,494 位,在「知識管理」分類(442 個)中排名第 300 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 34 | 1329 | - | - |
| SkillHub ↗ | 412 | 3261 | 1 | — |
各平台的計數口徑不同,統計時間不一致。
支援文字、Word、PDF 和 Excel 檔案;提取依賴 Python 及對應格式包,需獲得本地檔案讀取和 Python 執行許可權。提取內容會傳送給模型,文件明確不用於敏感或機密檔案。
資料釋出於 2026-10-27
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-09 | 3261 | — | 1 |
| 2026-08 | 2521 | +18.9% | 1 |
| 2026-07 | 2121 | +25.2% | 1 |
| 2026-06 | 1694 | +21.4% | 1 |
| 2026-05 | 1395 | — | 1 |
| 2026-03 | 833 | — | - |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。
--- name: file-summary description: | local document summary & analysis tool. triggers: 帮我总结, 总结文件, 分析文档, 分析总结, 总结一下, 分析一下 summarize for me, analyze for me, summarize the file, analyze the document, file summary, document analysis Supported formats: txt, docx, pdf, xlsx, xls ⚠️ Privacy Note: Extracted content will be sent to OpenClaw LLM for summary/analysis — DO NOT use with sensitive/confidential files. ---
# File Summary & Analysis Tool (文件总结与分析工具)
A universal tool for extracting text from local documents and generating summaries/analysis, supporting both Chinese and English trigger words.
## Token Extraction (参数提取)
### Chinese Input Example (中文示例)
From user input `帮我总结 D:\测试.pdf` → `file_path` = `D:\测试.pdf`
### English Input Example (英文示例)
From user input `summarize for me C:\test.pdf` → `file_path` = `C:\test.pdf`
## Actions (操作指令)
### Extract Document Content (提取文档内容)
{ "action": "extract", "file_path": "D:\\测试.pdf" }
{ "action": "extract", "file_path": "C:\\test.pdf" }
Returns (返回结果):
- Success: Plain text content of the document (txt/docx/pdf/xlsx/xls)
- Error: Error message starting with ❌ (e.g. ❌ File not found, ❌ Unsupported format)
### Generate Summary/Analysis (生成总结/分析)
{ "action": "summary", "file_path": "D:\\测试.pdf" }
{ "action": "analysis", "file_path": "C:\\test.pdf" }
Returns (返回结果):
- Summary: Concise key-point summary of the document content (integrated with OpenClaw LLM)
- Analysis: In-depth analysis of the document content (integrated with OpenClaw LLM)
## Workflow (工作流程)
To summarize/analyze a local document:
1. Extract content: `{ "action": "extract/analysis", "file_path": "your_file_path" }` → returns plain text
2. Generate result: OpenClaw LLM summarizes/analyzes the extracted text automatically
## Configuration (配置项)
channels:
local:
tools:
file_summary: true # default: true
python: true # required - need Python environment
## Dependency (依赖环境)
### Required Environment (必备环境)
1. Python 3.8+ (added to system environment variables)
2. Required Python packages (auto-installed by script):
- python-docx (for docx)
- pypdf (for pdf)
- openpyxl (for xlsx)
- xlrd==1.2.0 (for xls)
### Tool Path Configuration (工具路径配置)
1. Place the tool files in OpenClaw's skill folder:
OpenClaw/skills/file-summary/
├─ SKILL.md (this file)
├─ file2sum.py
2. Set the execution command in OpenClaw:
${skill_path}\\file2sum.py
## Permissions (权限要求)
Required (必备):
- Local file read permission (user needs to grant file access)
- Python execute permission (no special system permissions required)
## Usage (使用方法)
### Local Deployment (本地部署)
1. Put the `file-summary` folder into OpenClaw's `skills` directory
2. Restart OpenClaw
3. Input Examples (输入示例):
- Chinese (中文): "帮我总结 D:\测试.pdf", "分析文档 C:\数据\销售表.xlsx"
- English (英文): "summarize for me C:\test.pdf", "analyze the document D:\data\sales.xlsx"
### Public Deployment (公开发布)
1. Upload the `file-summary` folder (include md/py) to a public platform (e.g. GitHub/Gitee, ClawHub)
2. Share the download link
3. Users import via OpenClaw "Skill Market → Import from URL"把長文字、文件與網頁內容壓縮成要點和關鍵詞的摘要工具。
透過 IMA OpenAPI 管理筆記與知識庫內容。
規定如何為網頁請求選擇合適工具的必讀指引。
呼叫百度 AI 搜尋介面做網頁檢索的技能。
用 uvx 直接呼叫 markitdown,把各類檔案轉成 Markdown。
面向 OpenClaw 的預設網頁搜尋,即時檢索多個引擎。
用 DuckDuckGo 介面做網頁、新聞、圖片與影片檢索的技能。
檢索並發現可用 OpenClaw 技能的技能。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。