Bidder Reference Report Generation

Problem Scenario for Bidders

During the bidding preparation phase, bidders need to rapidly understand the procurement behaviors of potential clients, competitors, or partner agencies. However, related data on purchasing demands, historical awards, contract dynamics, and corporate relationships is often scattered across various public platforms. Manual collection and analysis are inefficient and prone to overlooking key decision-impact signals, such as recent repeated purchases, upcoming contract expirations, or specific agency preferences.

How the Skill Works

This skill employs a structured data acquisition and analysis workflow to generate a formal reference report tailored for bidding decisions. Its core capabilities and steps include:

1. Input and Scenario Clarification: The skill first obtains the target company name and the bidder's own focus area, defaulting to the "seeking bidding opportunities" scenario. It supports analyzing different roles, such as procurement parties, competitors, or agencies.
2. Structured Data Collection: Through calls to multiple internal APIs (e.g., POST /bid/companyProfileSummary, POST /bid/searchProjectApi), it sequentially retrieves the target's basic information, recent bidding projects, contract data, upstream/downstream relationships, and contact clues. The process strictly adheres to deduplication rules (e.g., using id + publishTime) and pagination strategies.
3. Layered Analysis and Report Generation: The skill organizes raw data into three layers: "factual data," "statistical summaries," and "bidding recommendations." For instance, it extracts high-frequency categories and amount ranges from procurement demands, identifies competitors from historical awardees, and transforms signals like contract expirations or repeated purchases into specific "opportunity pools" and "follow-up calendars."
4. Deliverable Standardization: The final output is a complete Markdown report containing a decision summary, key metrics dashboard, opportunity matrix, and action checklist, which is then converted into a business PDF with a "Shipu Technology" watermark. The report meticulously hides all technical implementation details and uses objective, cautious formal language.

Boundaries and Considerations

• Input Dependency: Report generation relies on the accuracy of the target company name provided by the user. The skill will flag risks associated with abbreviations but will not autonomously merge legal entities.
• Data Scope and Authority: All analyses are based on public bidding and contract data obtained through a specific service, constituting "factual data." Historical awards do not imply future trends; information such as contacts and phone numbers within the report must be manually verified before use in business communications.
• Advisory Nature of Recommendations: The "bidding recommendations" and "opportunity ratings" output by the skill are based on sample statistics and include cautious phrasing like "indications exist" or "requires further verification." They aim to provide decision reference, not definitive conclusions or professional due diligence.
• Format and Styling: The default deliverables are two files (Markdown and PDF). The PDF undergoes rendering checks to ensure no garbled text or truncation. The report avoids stating statistical indications as established facts.