AgentSkillsCN

policy-document-parser

从PDF文档中提取并整理公司政策信息，尤其是针对不同目的地设有上限的差旅费用政策。该技能会读取政策PDF，提取按地点与员工层级划分的费用限额等结构化数据，并将政策表格转换为机器可读的格式，以实现自动化校验。

SKILL.md
--- frontmatter
name: policy-document-parser
description: Extracts and structures company policy information from PDF documents, particularly travel expense policies with destination-specific caps. Reads policy PDFs, extracts structured data about expense limits by location and employee level, and converts policy tables into machine-readable formats for automated validation.

Policy Document Parser

When to Use

Use this skill when you need to:

  • •Analyze company policy documents (PDF format)
  • •Extract structured expense limits from travel policy tables
  • •Parse destination-specific caps by employee level
  • •Convert policy tables into machine-readable formats (JSON/CSV)
  • •Prepare policy data for automated expense validation systems

Core Workflow

1. Initial Setup & Document Discovery

  • •Scan the workspace for policy documents (typically PDF files)
  • •Identify the main policy document (look for files like policy_en.pdf, travel_policy.pdf, etc.)
  • •Use filesystem-list_directory to explore the workspace structure

2. Policy Document Analysis

  • •Read the PDF document using pdf-tools-read_pdf_pages
  • •Extract the full text content for analysis
  • •Identify the document structure and locate policy tables

3. Table Extraction & Parsing

  • •Focus on sections containing destination-specific expense caps
  • •Look for tables with the following structure:
    • •Destination cities/countries
    • •Employee levels (L1, L2, L3, L4, etc.)
    • •Category caps (Accommodation, Meals, Transportation, Communication, Miscellaneous)
    • •Per-day or per-trip limits

4. Data Structuring

  • •Convert extracted tables into structured JSON format
  • •Organize data by: city → employee_level → category → limit
  • •Include global rules (receipt thresholds, airfare policies, etc.) as separate metadata

5. Output Generation

  • •Create machine-readable policy files (JSON preferred)
  • •Generate summary reports of extracted policy limits
  • •Prepare data for integration with expense validation systems

Key Patterns from Trajectory

Document Structure Recognition

The policy PDF typically contains:

  1. •Header with policy name, effective date, currency
  2. •Global rules section (airfare, receipt thresholds, exceptions)
  3. •Destination-specific tables with caps by employee level
  4. •Multiple pages with consistent table formatting

Data Extraction Strategy

  • •Extract all pages first to understand full document scope
  • •Look for patterns like "Destination-Specific Caps" headers
  • •Parse tables with city names followed by level-based caps
  • •Capture per-day vs per-trip limits (Transportation vs Communication/Miscellaneous)

Error Handling

  • •Handle missing or malformed tables gracefully
  • •Validate extracted data against expected structure
  • •Log parsing issues for manual review

Output Formats

Primary Output: Structured Policy JSON