Claude Code Intelligent Skill: Automated Workflow for Hedge Fund PPM Analysis

This project builds a professional hedge fund research skill set for Claude Code. Using a sub-agent architecture, it enables batch automated analysis of Private Placement Memorandums (PPM), reducing document processing time from hours (traditional method) to minutes. Core components include: the analyzing-fund-ppm skill (extracts key clauses to generate standardized reports), the ppm-extractor sub-agent (isolated parallel processing), and the /process-ppms command (batch coordination). It addresses the pain points of analysts' repetitive work by integrating domain knowledge with AI technology.

In the hedge fund sector, PPM is a key document (50-100 pages, containing core information such as investment strategies and fees). Analysts face the following challenges when processing PPMs: tedious information extraction (need to locate key clauses from legal texts), inconsistent formats (difficult to standardize), batch processing difficulties (low manual efficiency), and unstable output quality (variations among analysts). AI Agent technology provides the possibility to automate such processes.

The project uses Skills and Sub-agents to solve the problems of large models' temporary processing (context limitations, format drift, no audit, difficulty in scaling). Skills encapsulate domain knowledge, operation processes, and output templates; Sub-agents enable isolated execution (avoid cross-contamination), parallel processing (parent agents can schedule multiple tasks simultaneously), fault tolerance (single failure does not affect the whole), and resource management (clean up context after tasks).

The analyzing-fund-ppm skill can extract structured information from PPMs (fund basic information, investment clauses, fee structure, liquidity clauses, key personnel, service providers, etc.) and generate professional Word reports. The reports include 10 chapters such as executive summary, fund structure, investment strategy, fee analysis, and liquidity analysis, with standardized formats for easy horizontal comparison.

The tool is applicable to: fund screening and preliminary selection (quickly extract information for comparison), due diligence support (serve as basic documents for in-depth analysis), investment committee reporting (directly use professional reports), and competitor analysis (batch process competitors' PPMs for horizontal comparison).

Notes to consider: Legal disclaimer (reports are for reference only and do not constitute investment advice; key clauses need to be confirmed by legal counsel), accuracy boundaries (misunderstanding of complex clauses, context-dependent errors, difficulty in handling non-standard formats), data privacy (comply with institutional security policies, do not send sensitive information to public APIs, and manage documents properly).

Future plans include expanding skills (e.g., polish-meeting-notes, fund-investment-dd, etc.) and adding JSON output mode to support cross-fund comparison. The open source value of the project: domain AI application example, Claude Code best practices, financial document processing solution, and community can contribute new skills and knowledge.