get_dapa_organization
Retrieve detailed information about a Korean defense acquisition organization by its official name or alias.
Instructions
방위사업청 조직명 또는 별칭으로 조직 상세를 조회합니다.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | 조직명 또는 별칭 |
Retrieve detailed information about a Korean defense acquisition organization by its official name or alias.
방위사업청 조직명 또는 별칭으로 조직 상세를 조회합니다.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | 조직명 또는 별칭 |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the method of lookup (by name or alias) but does not go beyond that; no contradictions exist.
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, tightly written Korean sentence that conveys the resource, the lookup key, and the operation. Every word earns its place; there is no redundancy or filler.
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?
For a simple, read-only lookup tool with one well-documented parameter and rich safety annotations, the description is complete enough for an agent to select and invoke it correctly. No output schema exists, but the phrase '조직 상세' sufficiently indicates the return is organization detail information.
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%: the single required parameter 'query' is already documented as '조직명 또는 별칭' (organization name or alias). The description essentially restates this same meaning without adding format, examples, or disambiguation guidance, so it adds no new semantic value 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 uses a specific verb ('조회합니다' - retrieves) with a clear resource ('방위사업청 조직 상세' - DAPA organization details) and a clear lookup method (by organization name or alias). It is unambiguous and distinct from the legal/policy-focused sibling tools, though it does not explicitly contrast itself with any sibling.
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 description provides no guidance on when to use this tool versus alternatives, no exclusions, and no context about when this lookup is appropriate. The sibling names imply it is organization-related rather than legal/policy-related, but that inference is left entirely to the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/ai-studying-man/DAPA-MCP'
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