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a7512cs

mcp-server-104

by a7512cs

用名稱找 104 公司

find_company

Find a company on Taiwan 104 job bank by name and get its companyId, industry, region, employee count, capital, and open job count. Returns a single match or candidate list for multiple matches.

Instructions

用公司名稱找 104 上的公司,回傳公司名片:companyId(公司代碼,可直接餵給 get_company_jobs)、全名、公司頁網址、產業、地區、員工數、資本額、在徵職缺數。比對是模糊的:英文別名(如 MediaTek)也找得到中文本尊,但 total 含「簡介提及」的公司會偏大。唯一命中或名稱完全相符 → 回單一 company;多家符合 → 回 candidates 候選清單,此時請向使用者確認是哪一家(用產業/地區/在徵職缺數分辨),不要自行猜選。「某公司有沒有某類職缺」的標準流程:find_company 拿 companyId → get_company_jobs 帶 keyword。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes公司名稱 —— 全名、常用簡稱或英文名皆可,如 '聯發科'、'台積電'、'MediaTek'

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden; it discloses fuzzy matching, the total count caveat for introduction mentions, and the single-vs-candidates decision rule. It does not state what happens when no company matches, which is a minor but relevant gap.

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

Conciseness5/5

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

The description is front-loaded with the core action and output, then moves through matching behavior, user-confirmation guidance, and the downstream workflow in a logical order. Every sentence carries operational value with no redundant filler.

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?

For a one-parameter tool with no output schema and no annotations, it covers the input contract, output fields, ambiguous-result handling, and integration with get_company_jobs. The only notable omission is the no-match return behavior; otherwise an agent has enough to call it correctly.

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

Parameters4/5

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

The single name parameter is already fully described in the schema with full-name/abbreviation/English examples, so schema coverage is 100%. The description adds extra meaning by explaining alias matching and fuzziness, which helps the agent understand acceptable inputs and edge cases.

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?

The description states the tool finds companies on 104 by name and enumerates the returned 'company card' fields, including the companyId that feeds get_company_jobs. This clearly defines the verb+resource and distinguishes it from job-search siblings.

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

Usage Guidelines4/5

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

It explicitly prescribes the standard flow for checking whether a company has certain job types (find_company → get_company_jobs with keyword) and tells the agent to confirm with the user rather than guess when multiple candidates appear. It does not explicitly contrast with search_jobs or get_job_detail, but the intended use case is clear.

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