About this skill

Problem

Due diligence, lead preparation, and customer background checks often require structured data about mainland Chinese companies: registration details, legal representatives, business scopes, contact channels, and sometimes judicial or IP-related fields. Manually checking multiple portals is slow, and ad-hoc web searches often return unstructured snippets that are hard to verify. This skill connects the Bainiu business query workflow to an agent, making it useful when you already have company names and need results that can be processed further.

How It Works

The workflow has three main parts:

API setup: the first run needs a BAINIU_API_KEY, typically copied from .env.example into .env.
Single-company queries: identify the right tool with find_tool.js, which returns the tool ID, description, parameters, and match score; then call the selected tool using key=value arguments rather than JSON strings.
Batch basic-info export: for five or more companies whose requested fields are basic registration or contact data, upload a .txt file with one company name per line to receive an Excel download link.

The design favors direct single-tool calls when one tool can satisfy the request, instead of combining multiple partial tools. Within the same session, a returned tool_id can be reused. Batch responses include remaining quota; if an export is incomplete and returns code: "238", reduce the number of companies and tell the user. For failures, distinguish authentication issues, missing results, and empty data; use fuzzy search to confirm company IDs and fall back to web search when needed.

Boundaries

This skill is best for structured queries on mainland Chinese companies and batch exports of basic company information. It is not intended as the only path for judicial risk, intellectual property, or detailed operational data; use single-company queries for those fields. Tool availability changes dynamically, so rely on the actual find_tool.js output. Batch files must be .txt files, contain one company name per line, and stay under 10,000 lines; split larger lists. Clean up generated temporary files, but do not delete user-provided input files.

Screenshots

Use Cases

Lead cleaning: batch-query candidate companies for Unified Social Credit Codes, legal representatives, and contacts, then export Excel.
Initial due diligence: compare registration, registered capital, address, and business scope for five or more target companies.
Single-company checks: before negotiations or signing, use find_tool to match and call judicial, IP, or operational data tools.
Customer background: collect a Chinese company's contacts, business scope, and registered address into due-diligence notes.

Best For

Sales or BD: batch-verify candidate companies' USCC, contacts, and business scope to build a contactable list.
Due-diligence or risk analysts: compare companies' registration, capital, address, and scope to prepare an initial workpaper.
Operations or marketing: collect one Chinese company's contacts, business scope, and registered address for customer background checks.
Data analysts: integrate Bainiu query results into analysis workflows and process structured company fields.