get_companyFetch one company's full record by country code and registration number, legal name, status, entity type, incorporation date, registry source, and any officers held.
| Name | Required | Description | Default |
|---|---|---|---|
| country | Yes | ISO-2 country code, e.g. NG. | |
| registration_no | Yes | The registry number (RC / RCCM / file no.). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The verb 'fetch' implies a read operation, and the description lists returned fields, which is useful. With no annotations, it does not explicitly state read-only nature, error behavior, or permissions, leaving gaps.
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?
A single, well-structured sentence that front-loads the action. The field list adds length but provides valuable output context, making it appropriately concise.
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 tool with two parameters and no output schema, the description adequately covers invocation and return fields. It lacks explicit error/not-found behavior but is sufficient for basic selection and invocation.
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% with meaningful descriptions for both parameters. The description restates 'by country code and registration number' without adding deeper parameter semantics.
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?
Clearly states 'Fetch one company's full record' with specific identifiers (country code and registration number) and lists the returned fields, distinguishing it from siblings like search_companies and get_company_procurement.
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?
Provides clear context by requiring country code and registration number, implying use when these identifiers are known. However, it does not explicitly mention when not to use or name alternatives.
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 distinct purpose: search_companies finds companies, get_company fetches full records, get_company_procurement retrieves contract history, and screen_sanctions checks sanctions lists. There is no overlap or ambiguity between them.
All tool names follow a consistent verb_noun snake_case pattern: get_company, get_company_procurement, screen_sanctions, search_companies. The naming is uniform and predictable.
With 4 tools, the server is well-scoped for its purpose of company data lookup and compliance screening. Each tool covers a distinct, necessary function without redundancy or bloat.
The tool set covers the full lifecycle of company research: search, retrieve full record, retrieve procurement history, and screen against sanctions. Since this is a read-only data service, there are no obvious gaps unless additional compliance features (e.g., list screening) are expected, but the current coverage is sufficient for typical use cases.