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get_tender

單一標案的完整歷程:招標→決標的每則公告、預算與決標金額、得標廠商、 競爭態勢(幾家投標/是否單一投標)、是否為續約案、政府電子採購網的 招標文件領取頁與公告詳細內容頁網址,以及開標實況——決標公告揭露的 每一家投標廠商、各自標價、底價、未得標原因。 開標實況是別處查不到的:可以看出出價最低的為什麼沒得標。 另有 official_details:政府電子採購網公告的明細——招標方式、決標方式、是否訂有底價、截止投標、 開標時間與地點、押標金、是否電子投標、收受投標文件地點、履約地點與期限、後續擴充、廠商資格摘要、 是否受機關補助、聯絡窗口。日期為民國年。還在招標的案子第一次查可能要幾秒; 拿不到時看 official_details_note 的說明。 unit_id 與 job_number 來自 search_tenders 的結果列。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
unit_idYes
job_numberYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations the description carries the full burden, and it discloses notable behavior: first-time queries on still-bidding cases may take several seconds, a failure path points to official_details_note, and it flags that the bid-opening detail is data unique to this tool. It stops short of describing auth needs or output shape, but for a read tool this is solid disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the primary value (the full lifecycle and the unique bid-opening detail) before the long enumeration of official_details fields. It is dense but every clause conveys concrete returned data rather than filler; slightly verbose in the official_details list.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description does the heavy lifting well, enumerating returned fields, competition metrics, and external URLs, plus latency and failure handling. It is nearly complete for a single-record fetch tool; only return structure/format nuances remain unspecified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% for two required params, so the description must compensate. It does explain the provenance of unit_id and job_number (from search_tenders result rows) but never clarifies what each identifier actually denotes, adding origin information without full semantic meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource (retrieve one tender's complete lifecycle from tender announcement to award) and enumerates exactly what it returns: every announcement, budget/award amounts, winning vendor, competition intensity, renewal status, URLs, and bid-opening details. It also distinguishes itself from search_tenders by noting unit_id/job_number come from search_tenders result rows.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It establishes the prerequisite relationship to search_tenders (inputs come from its result rows) and gives a debugging hint (see official_details_note when data can't be fetched). However, it never states when to prefer this over siblings like vendor_report, price_analysis, or compare_vendors, leaving usage largely implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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