Generates a narrative business overview covering a company's operations, products, and target market using data from its website and LinkedIn profile.
Produces a narrative business overview (what the company does, products/services, target market) sourced from the company's own site and LinkedIn.
| Name | Required | Description | Default |
|---|---|---|---|
| context | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds that the overview is sourced from the company's own site and LinkedIn, which is useful behavioral context about data provenance. However, it does not disclose limitations (e.g., private companies may have sparse data) or any failure modes, so it adds moderate value beyond annotations.
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 sentence, which is concise and front-loads the core purpose. However, it omits critical usage and parameter information, so it does not fully earn its place. It is not overly verbose, but the missing details make it less effective than it could be.
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?
Given the nested context object, multiple optional parameters, and no output schema, the description is incomplete. It does not explain how to provide the company (e.g., via context.company), how to use companyDomain, or the significance of country or sector. The agent is left with insufficient information to correctly invoke the tool beyond the schema names.
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?
The description does not mention any parameters at all. Schema description coverage is 0% (the description does not explain any of the inputs). The required context object and its sub-properties (company, companyDomain, country, etc.) are left entirely to the schema. The description fails to compensate for the lack of parameter documentation, so an agent has no guidance on how to specify the target company or domain.
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 tool produces a narrative business overview (what the company does, products/services, target market) and identifies sources (company's own site and LinkedIn). The verb 'produces' is specific, and the resource is the company overview. It distinguishes from siblings like industry_overview or market_size by focusing on a single company, but does not explicitly differentiate from company_profile, so it's clear but not perfectly distinguished.
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?
No guidance is given on when to use this tool versus alternatives like company_profile or industry_overview. It does not state any conditions, exclusions, or mention sibling tools. The agent is left to infer when this is the right choice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.