Find customer company IDs by searching partial names. Enter a name fragment to retrieve matching customers and resolve name-to-ID mapping for JDRA issue creation.
고객사를 조회한다(이름→id 해석용). query 로 이름 일부 필터.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | 고객사 이름 일부 (생략 시 전체) |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. '조회한다' signals a read-only operation, and '일부 필터' discloses partial matching behavior. However, it does not mention response shape, edge cases, or pagination, which is a moderate gap for a tool without an output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single compact sentence that front-loads the core purpose and then states the filtering syntax. It has no filler words or repetition of schema details, making it efficient for an agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With only one optional parameter and no output schema, the description provides sufficient orientation for the expected use case. It indicates the return purpose (name→id mapping) and the filter semantics. It could be more explicit about the exact output structure, but the core calling context is well covered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents the 'query' parameter, including its optionality and meaning. The description only restates that the query filters by partial name, adding no new parameter-specific detail beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('조회한다'), the resource ('고객사'), and a specific intended use case ('이름→id 해석용'). This distinguishes it from sibling search tools like jdra_search_users or jdra_search_projects by naming the entity type and purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase '이름→id 해석용' gives a clear context for when to call this tool: when converting a customer name to an ID. It implies the use case without explicitly naming alternatives, so no explicit exclusions are present, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.