Bid Data Search Radar

要解决的具体问题

Searching for bidding data often involves navigating fragmented sources across thousands of websites with inconsistent formats, leading to time-consuming manual filtering. Keyword matching can miss relevant projects, and opportunity discovery relies on experience without systematic tracking. Engineers face challenges in locating bids by specific industries, regions, or budget ranges, often switching between multiple platforms inefficiently.

技能如何工作

核心能力

Built on Shibo Technology's bidding data API, this skill provides the following core capabilities:
- Natural Language Search: Uses the SearchProjectForAI interface to convert conversational queries (e.g., 'smart campus equipment procurement in Beijing over the past 30 days') into structured search conditions, reducing technical barriers.
- Multi-Dimensional Structured Filtering: Supports queries by region, industry, keywords, procurement units, winning units, project IDs, budget ranges, and time frames, covering procurement intentions, bid announcements, winning results, and contract announcements.
- Deep Data Parsing: Returns results with fields like project name, buyer, winner, budget/win amount, announcement phase, source link, among 78 structured fields, enabling quick analysis of procurement trends and supplier dynamics.
- AI-Assisted Reasoning: Employs the industryReasoning interface to automatically infer industry codes or directions from keywords, enhancing search accuracy.

关键步骤

The workflow follows a logical chain typical of technical blogs:
1. Intent Recognition and Condition Extraction: Parses user questions to extract elements like region, industry, and amount, identifying whether the intent is for bid, winning, or contract inquiries.
2. Query Construction and Search: For colloquial expressions, first rewrites queries via SearchProjectForAI; otherwise, directly calls interfaces like searchProjectApi to execute searches.
3. Result Organization and Delivery: Outputs a brief conclusion first (e.g., hit count, time range), lists key projects in a table, and provides suggestions such as viewing details, tracing sources, or expanding the time range.
4. Exception Handling: In case of insufficient balance (error code 0100590006), prompts users to purchase packages and waits for confirmation without automatic retries.

适用边界或注意点

• Strict Interface Limitations: Only uses listed interfaces (e.g., SearchProjectForAI, searchProjectApi, industryReasoning), does not add specialized interfaces for healthcare, education, or other industries, and avoids unauthorized tools.
• Data Dependency and Keys: Requires configuration of the BBIAO_API_KEY environment variable for authentication; keys must be stored securely and never auto-registered or guessed. Guidance is provided if keys are missing.
• Information Accuracy: Search results are based on existing data; no guarantees on winning bids or fabricated facts. Fields like amounts, times, project IDs, or source URLs are kept as-is without speculation.
• Use Case Boundaries: Suitable for quick project discovery and preliminary screening; deeper analysis may require additional tools. Does not cover non-bidding domains or complex business intelligence beyond competitor analysis.