Hospital IT Project Bid Assistant

The Core Challenge of Tender Information Retrieval

In the hospital IT sector, tender information—whether one is looking for potential supplier opportunities or analyzing the procurement preferences and historical awardees of a specific buyer (e.g., a hospital)—is often scattered across various platforms like different public resource trading centers and procurement websites. Engineers and market analysts face the problem of dispersed data sources, where manual, one-by-one queries are highly inefficient, and unstructured information, where key fields like project name, procurement amount, winning bidder, and announcement phase must be manually extracted from voluminous web page text, making systematic analysis difficult.

The Hospital IT Project Bid Assistant is designed precisely to solve these issues. It automates the process of retrieving, extracting, and performing initial analysis on this scattered data by integrating with Shibo Technology's nationwide, cross-industry tender data API.

How the Skill Works: Core Capabilities and Workflow

The skill's core is an information retrieval and structured analysis pipeline optimized for natural language queries. Its workflow is as follows:

1. Requirement Parsing and Condition Conversion: When a user inputs a query like "Find HIS system award projects in East China over the past six months with a value exceeding 5 million," the skill uses specialized AI interfaces like aiSearchSubmitPolling or SearchProjectForAI to decompose the colloquial request into structured query parameters, such as: keyword (HIS), region (East China), time range, amount range (>5 million), and announcement phase (award).
2. Intelligent Search and Whitelisted Calls: Based on the parsed conditions, the skill initiates requests exclusively using the whitelisted set of 6 interfaces (e.g., searchProjectApi for list searches). It automatically handles pagination (pageNumber), nationwide default queries (where areaCode is ["0"]), and initially filters out irrelevant "hiring," "training," etc., projects unrelated to "hospital IT."
3. Data Enrichment and Provenance: For key or ambiguous projects in the search results, the skill calls getZTBStructreDetail to retrieve structured details (buyer, awardee, amount, contacts, etc.) or getZTBProjectDetail to fetch the original announcement text. All displayed data must originate from the API's actual returned fields; missing fields are explicitly noted as "not returned."
4. Result Presentation and Recommendations: The final output typically includes a structured list (project name, buyer, amount, etc.) accompanied by next-step suggestions, such as "You could further query this buyer's historical procurement preferences" or "Obtain the project announcement's attachments for a detailed qualification review."

Application Boundaries and Key Considerations

• Dependency on Data Source and Permissions: The skill relies entirely on Shibo Technology's BBIAO_API_KEY for data access. Users must configure this key themselves (read from the environment variable BBIAO_API_KEY) and be mindful of their package quota. When the quota is insufficient (error code 0100590006), the skill will stop and prompt the user; it will not automatically recharge or retry.
• Query Scope and Accuracy: Its capability is strictly limited by the 6 whitelisted interfaces it calls; no new interfaces are added. The results cover public tender data but do not represent all projects in reality (an empty array only indicates no match for the current conditions). It is recommended to trace back to the original source for high-value conclusions.
• Intended Use Case: It specializes in the hospital IT and related domains (HIS, EMR, Smart Hospital, Medical Insurance Interface, etc.). Although the data source is cross-industry, its keyword library, industry filtering, and recommended queries are all optimized around this vertical. For completely unrelated industries, its retrieval effectiveness will be significantly diminished.