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lazymac2x

lazymac-mcp

k_company_lookup

Look up Korean companies using business registration numbers to verify corporate information and details.

Instructions

Korean company lookup by business registration number

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNoFree-form params object — passed as query string for GET, JSON body for POST
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does ('lookup'), without mentioning whether it's read-only or mutative, authentication requirements, rate limits, error handling, or output format. For a lookup tool with zero annotation coverage, this is a significant gap in transparency.

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 a single, efficient sentence that front-loads the core functionality. There's no wasted text, and it directly communicates the tool's purpose without unnecessary elaboration.

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

Completeness2/5

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

Given no annotations, no output schema, and a single but nested parameter, the description is incomplete. It doesn't cover behavioral aspects like safety, authentication, or rate limits, nor does it hint at return values or error conditions. For a lookup tool in a data-rich context, more guidance is needed.

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?

The input schema has 100% description coverage, with one parameter ('params') documented as a free-form object for query strings or JSON bodies. The description adds value by specifying the key input ('business registration number'), but doesn't explain parameter structure, required fields, or format details beyond what the schema implies. This meets the baseline for high schema coverage.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Korean company lookup by business registration number'. It specifies the action (lookup), resource (Korean company), and key parameter (business registration number). However, it doesn't differentiate from sibling tools like 'k_business_validator' or 'k_public_data', which might offer similar or overlapping functionality.

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

Usage Guidelines2/5

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. It doesn't mention sibling tools like 'k_business_validator' or 'k_public_data', nor does it specify prerequisites, exclusions, or ideal use cases. The agent must infer usage from the name and description alone.

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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