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基金月报信息提取
by
Yujing2013
· GitHub ↗
· v2.3.0
· MIT-0
285
Downloads
0
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0
Active Installs
8
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Install in OpenClaw
/install mutual-fund-monthly-update
Description
基金月报信息提取。支持单文件上传和批量处理文件夹。自动学习Excel模板,从PDF月报提取数据,生成两份Excel(PDF信息Excel + 用户模板Excel)。
Usage Guidance
This skill appears coherent and implements local PDF→Excel extraction. Before using it: (1) install Python deps in a virtualenv and install system packages (tesseract, poppler) as documented; (2) do not point the skill at system or sensitive folders—only provide folders containing the monthly reports you want processed; (3) run it in an isolated/test environment first to confirm OCR accuracy and template mapping (OCR can misread chart text); (4) verify generated Excel files for correctness; (5) note the skill may call local binaries (tesseract, pdftoppm) when OCR is used, but it makes no network calls and does not request credentials. Finally, the SKILL.md reference version differs slightly from registry metadata—this is benign but you may want to confirm you have the intended version.
Capability Analysis
Type: OpenClaw Skill
Name: mutual-fund-monthly-update
Version: 2.3.0
The skill bundle is a legitimate tool designed to automate the extraction of financial data from mutual fund PDF reports into Excel templates. It utilizes standard Python libraries such as pdfplumber, openpyxl, and pytesseract for data processing and OCR, with no evidence of network activity, data exfiltration, or unauthorized command execution. The scripts (auto_update_final.py and update_fund_excel.py) and the extensive documentation in the references/ directory are focused entirely on the stated purpose of fund data management and include appropriate safety measures like temporary directory cleanup.
Capability Assessment
Purpose & Capability
Name/description match the included scripts and reference docs: the Python scripts and references implement PDF text extraction, optional OCR, template learning, and Excel generation. Required tools (pdfplumber, openpyxl, pdf2image, pytesseract) are appropriate for the described functionality.
Instruction Scope
SKILL.md and the references strictly describe reading user-provided PDFs/Excel and writing output Excel files. The code only touches files in user-specified paths or temporary directories; there are no instructions to read system credential files, user profiles, or other unrelated data. The batch-processing behavior (scan a user-specified folder) is documented and consistent with the skill purpose.
Install Mechanism
This is instruction-only (no automated installer). The docs require several Python packages and system binaries (Tesseract, Poppler). Those are reasonable for OCR/PDF processing, but they are system-level dependencies and must be installed manually (not provided by the skill). Users should install them in a virtual environment and ensure the platform supports running tesseract/pdftoppm.
Credentials
The skill requests no environment variables, no credentials, and no config paths. All file I/O is limited to user-supplied folders and temporary dirs. There are no unrelated secrets or external service tokens requested.
Persistence & Privilege
The skill does not request permanent presence or elevated privileges (always=false). It writes output files to user-specified locations (or a documented default remote output path), and learning state is described as ephemeral/in-memory. No system-wide configuration changes are performed.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install mutual-fund-monthly-update - After installation, invoke the skill by name or use
/mutual-fund-monthly-update - Provide required inputs per the skill's parameter spec and get structured output
Version History
v2.3.0
Version 2.3.0
- Added extraction_templates.json to the references directory for managing extraction templates.
- Lays groundwork for more flexible or extensible extraction workflows in future updates.
v2.2.2
- 增加用户批量上传文件的交互提示,需用户发送“好了”后才开始处理,防止文件遗漏
- 新增 interaction_rules.md 文档,详细说明文件交互规则
- 新增 SECURITY_REVIEW.md,补充安全评估说明
- references/ 目录补充交互和安全相关内容
v2.2.1
## v2.2.1 Changelog
- Removed deprecated scripts: auto_update_v2.py and auto_update_v3.py.
- No changes to user functionality or core features.
v2.2.0
**新增批量处理文件夹功能,优化多基金多时点自动分类及模板应用:**
- 支持通过“请处理这个文件夹:/path/to/folder/”一次性批量处理文件夹内全部PDF,自动按基金名分Sheet、同基金多时点升序排列。
- 新增并重构 references 文档(字段映射、模板学习、OCR规则、批量处理说明),移除旧有静态模板/数据文件。
- 自动检测并应用用户Excel模板,实现精准字段映射、样式及数据类型保持。
- 提取流程双通道(文本+OCR),所有分布数据均强制识别提取,提升数据准确性和完整性。
- 输出两份Excel:AI自由格式及用户模板格式,便于核查和后续处理。
v1.0.3
Version 1.0.3
- 更新安全说明,明确首次运行可能自动 pip 安装依赖包时需要网络,后续处理全部本地完成。
- "权限范围"增加对初次安装网络需求的提示,并补充“网络使用”说明,强调仅首次安装需要网络。
- 明确“不会上传PDF或Excel内容到服务器”,细化数据仅本地处理的安全说明。
- 其它功能、输出方式、依赖要求等内容无变动。
v1.0.2
mutual-fund-monthly-update v1.0.2
- 新增 requirements.txt 文件,明确各项 Python 依赖。
- 明确依赖项:pdfplumber、openpyxl(文本/表格提取)、pytesseract、Pillow(可选,OCR)。
- 技能说明文档优化,增加了依赖、环境和安全说明,并补充首次使用友好提示。
- 未涉及代码和功能修改,仅补充和完善依赖管理与使用说明。
v1.0.1
- 重大升级:支持多基金和多期横向对比,全面增强数据提取与格式输出灵活性。
- 新增多基金+多期Excel横向对比功能,自动按基金分组、分Sheet输出。
- 支持自定义模板输出,可学习用户上传Excel模板样式、配色、布局等,实现无缝格式对接。
- 强化OCR自动切换:无法文本提取时自动启用OCR,遇图表/饼图自动提示识别效果和局限。
- 通用化数据提取能力,用户可自定义提取任何PDF中有的数据内容。
- 文件结构优化,简化配置依赖,更便于模板及示例的动态管理。
v1.0.0
- 支持自动识别并提取互认基金月度Excel和PDF报告内容,实现月度数据更新流程自动化
- 新增OCR功能,自动识别PDF中的行业分布与区域分布(首批支持华夏基金)
- 支持多种提取方式,包括主题定向内容查询、ZIP打包批量处理、独立文件上传
- 返回方式灵活,支持导出Excel、生成飞书文档/表格等
- 已支持14家主要基金的核心指标与结构化数据提取,并支持数据映射和模板配置
- 保证Excel公式与格式安全,只更新指定数据区域
Metadata
Frequently Asked Questions
What is 基金月报信息提取?
基金月报信息提取。支持单文件上传和批量处理文件夹。自动学习Excel模板,从PDF月报提取数据,生成两份Excel(PDF信息Excel + 用户模板Excel)。 It is an AI Agent Skill for Claude Code / OpenClaw, with 285 downloads so far.
How do I install 基金月报信息提取?
Run "/install mutual-fund-monthly-update" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is 基金月报信息提取 free?
Yes, 基金月报信息提取 is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does 基金月报信息提取 support?
基金月报信息提取 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created 基金月报信息提取?
It is built and maintained by Yujing2013 (@yujing2013); the current version is v2.3.0.
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