get_companyRetrieve a Kansas City company's profile by ID, including headquarters, typical roles, in-demand skills, and current open job listings.
Fetch one KC company by its id (slug, from list_companies): overview, headquarters, typical roles, the skills it hires for most, and its current open roles.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The company id/slug returned by list_companies. |
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 itself must convey the operation's nature. 'Fetch' clearly communicates a read-only actionaging non-destructive, and the description enumerates exactly what is returned. It does not mention error conditions or rate limits, but for a simple fetch these are minor.
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?
Single dense sentence that states the action, the key parameter, and the return contents. No wasted words.
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?
The tool has one parameter, no annotations, and no output schema. The description covers the input source, the action, and the full list of returned fields, which is sufficient for an agent to decide to call it and interpret the result.
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 already describes the id parameter, and the description reinforces it as a slug from list_companies. This adds useful sourcing context beyond the schema's description without being redundant.
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?
Description uses a specific verb+resource ('Fetch one KC company by its id') and names the exact returned fields (overview, headquarters, typical roles, skills, open roles). This clearly distinguishes it from siblings like list_companies (plural listing) and get_job (job-specific).
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?
Description explicitly states the input is the slug from list_companies, teaching the agent that get_company is the follow-up to a list operation. It does not explicitly mention exclusions or alternatives, but the id provenance and singular scope imply the right usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.