get_company_by_domainResolve a company domain (e.g. 'walgreens.com') to its full profile: firmographics, hiring stats, and the technology stack with adoption context (using / adopting / replacing / evaluating).
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Company primary domain |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and idempotent behavior. The description adds valuable context about the output contents (firmographics, hiring stats, tech stack adoption context), aligning with the annotations. No contradictions.
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 sentence with no filler. Action is front-loaded ('Resolve a company domain'), includes a concrete example, and lists output categories concisely. Every word serves a purpose.
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 tool's simplicity (one parameter, read-only, idempotent) and the descriptive content covering input and output categories, the description is complete. No output schema is needed as the list of return categories suffices.
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% for the single parameter 'domain'. The description adds clarity with an example ('walgreens.com') and explains that the domain is resolved to a full profile, which enhances meaning beyond the schema description.
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 specific verbs ('Resolve a company domain') and clearly distinguishes from siblings: it returns a full profile (firmographics, hiring stats, tech stack) while siblings focus on technology lists or searches. No ambiguity.
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 implies usage when a domain is known, but lacks explicit when-not-to-use or alternatives. Sibling tools are mentioned in context signals but not in the description, so guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: resolving a specific company, listing all technologies, or searching companies by technologies. There is no overlap or ambiguity.
All tool names follow a consistent verb_noun pattern in snake_case (get_company_by_domain, list_technologies, search_companies_by_technologies), making them predictable and easy to understand.
With 3 tools, the server is appropriately scoped for its purpose of providing technographic data. Each tool is essential and covers the primary operations needed.
The tool surface covers all obvious needs: retrieving company profiles, exploring the technology catalog, and searching for companies using specific technologies. There are no apparent gaps for a read-only technographics server.