Enterprise Due Diligence Report

Problem to Solve

Enterprise due diligence often stalls because data is scattered and conclusions are hard to reproduce. Company registration, equity, litigation, patents, bidding, financials, and public sentiment live in different systems. Manual reports can state a risk, but make it difficult to verify how control chains, hidden affiliates, or procurement scale were inferred. This skill is for engineers and due diligence workflows that need a publishable Markdown report with an auditable evidence chain.

How It Works

The skill uses Shuidi Credit MCP tools and organizes analysis into eight modules: company fundamentals, control and hidden ownership chains, founder profile, financing and capital, technology and IP, market and supply chain, risk and sentiment, and competitive landscape. Key steps include:

• Verify direct ownership, beneficial owners, and effective control using get_company_info, get_company_beneficial_owner, and pierce_equity.
• Map technical assets with search_patent, evaluate_sti_capability, and related IP tools, accounting for subsidiaries that may hold patents.
• Aggregate risk and public signals using search_company_risk and search_news, and cross-validate core conclusions.
• Convert the Markdown report to a PDF with cover, table of contents, page numbers, and chapter breaks via scripts/build_dd_report.py.

Each data point should carry its source, calculation method, and confidence level, separating fact from inference.

Boundaries and Notes

The skill depends heavily on configured Shuidi Credit MCP services. If shuidi_data or shuidi_risk is unavailable, control-chain and risk analysis may be materially degraded. Listed-company financial, supply-chain, and bidding modules may be marked as unavailable when data sources are missing. It is suitable for structured due diligence drafts, evidence-chain organization, and PDF delivery, but it does not replace legal advice, financial audit, or human review of real-time sentiment.