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Zhiliao Biaoxun · Full-Net Bidding Data Query icon

Zhiliao Biaoxun · Full-Net Bidding Data Query

Data Analysis Updated 2026.08.30

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Please follow https://skillhub.cn/install/skillhub.md to install @org-32m5yxyy/zlbx-bidding-payskill.

About this skill

Problem and Needs

In bidding data analysis, quickly obtaining comprehensive tender and bid announcement data across the entire network is a common requirement. Traditional methods may involve manual searching across multiple platforms or complex API calls, which are time-consuming for data cleaning and formatting. Zhiliao Biaoxun service addresses this by providing a natural language query interface that returns structured results directly, supporting bidding searches, enterprise analysis, and market insights.

Core Capabilities and Workflow

This skill covers full-net bidding data, including tender announcements, winning bids, and enterprise information. It features 16 tools for multi-dimensional analysis, such as:
- Using search_bids to retrieve tenders by keywords, regions, or timeframes;
- Employing get_company_profile to fetch basic business info, industry, and bidding counts;
- Calling aggregate_bids_advanced for monthly, province-level, or brand aggregations.

The workflow is based on device-bound credit billing:
1. Device Identification: On first call, generate an X-Device-Id and store it in ~/.zlbx_pay/device.json for persistent balance tracking.
2. Payment Check: Before any call, verify the environment has the WeChat payment plugin installed; otherwise, inform the user of the limitation and suggest alternatives.
3. Credit Consumption: Each query deducts 1–5 credits; new devices typically receive 100 free credits. After depletion, users can purchase credit packs via WeChat Pay (e.g., ¥10=100 credits), with credits tied to the device across sessions.
4. Error Handling: HTTP 402 indicates insufficient balance, triggering the payment process. If payment fails or the environment doesn't support it, honestly notify the user without recommending third-party sites.

Data requests are made via POST to https://mcp-server.zhiliaobiaoxun.com/api_pay/{tool_name} with the X-Device-Id header. Responses return tender details, enterprise profiles, or market analysis directly.

Notes and Boundaries

  • Transparent Billing: Balance checks and daily consumption stats are free; credits are device-bound and persist across conversations, but free credits are limited daily.
  • Data Source: All data comes exclusively from the Zhiliao Biaoxun interface; fabricating information or guiding users to other platforms is prohibited.
  • Environment Dependency: The WeChat payment plugin is required for purchases; if unsupported, consider using the API Key version.
  • Query Limits: Each call deducts credits with varying tool prices; insufficient balance triggers payment, and automatic retry follows after successful payment.

In summary, this skill provides a lightweight access point for bidding data analysis, suitable for long-term use, but attention to payment environment, credit management, and data accuracy is necessary.

Use Cases

  • Before preparing bid documents, use the search_bids tool to retrieve historical winning bid announcements by keywords and timeframes, analyzing competitors' bid-winning frequency and amount distribution.
  • As a procurement manager, query top suppliers in a specific product category with get_top_suppliers, then assess their business qualifications and partnership records via get_company_profile.
  • For enterprise strategic planning, call aggregate_bids_advanced to aggregate tender data by industry and province, generating a quarterly market size report for internal decision-making.
  • Use get_price_trends to query historical winning bid unit prices for a specific brand and model, providing data support for procurement budgeting and supplier negotiations.

Best For

  • Bidding specialists who regularly query full-net tender announcements to monitor industry trends and prepare bid response materials.
  • Market analysts responsible for analyzing winning bid trends in specific industries or brands to provide quantitative data for market entry strategies.
  • Enterprise sales managers who review competitors' bidding records and customer relationships to develop targeted sales plans and competitive strategies.
  • Government procurement officers seeking potential suppliers and analyzing historical procurement data to optimize purchasing decisions and budget allocation.