Verify a business entity — registration status, incorporation date, legal standing, and registered address. Data sourced from GLEIF, Companies House, SEC EDGAR, and OpenCorporates.
| Name | Required | Description | Default |
|---|---|---|---|
| entity_name | Yes | Company name to verify | |
| jurisdiction | Yes | ISO 2-letter country code (e.g. GB, DE, AE, US) | |
| registration_number | No | Company registration number (optional) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It does add useful context by naming the data sources and the kind of data returned. However, it does not mention potential discrepancies between sources, failure modes, coverage limitations, or what happens when an entity is not found.
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 efficiently written sentence with no filler. It communicates the target, the result, and the data provenance without repetition or unnecessary detail.
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 description is sufficient for an agent to understand the tool's purpose, the kind of data it returns, and where that data comes from. The schema covers parameter meanings. No output schema exists, but the description enumerates the main output concepts. Minor missing details such as error behavior and source-specific limitations prevent a perfect score.
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 input schema already provides full descriptions for all three parameters, giving 100% schema description coverage. The description adds context about what the tool does but does not add parameter-specific meaning beyond what the schema already documents.
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 that the tool verifies a business entity and enumerates the specific attributes it returns: registration status, incorporation date, legal standing, and registered address. While it does not name sibling tools, the verb and resource make its purpose evident and distinguishable from map_ownership, score_risk, and screen_sanctions.
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 this tool should be used when an agent needs registration-level verification of a business entity, but it does not explicitly say when to use it instead of alternatives or when not to use it. The sibling tool names suggest different purposes, but the guidance is left to inference.
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 targets a distinct intelligence function: ownership mapping, jurisdiction risk scoring, sanctions screening, and entity verification. While some data sources overlap, the purpose and output of each tool are clearly separable.
All tool names follow a consistent verb_noun pattern: map_ownership, score_risk, screen_sanctions, verify_entity. The verb clearly indicates the action and the noun clearly indicates the subject, making the naming predictable and intuitive.
Four tools is a well-scoped set for an entity intelligence API. Each tool covers a meaningful and distinct part of the domain without redundancy or bloat.
The core entity intelligence workflow is covered: verify the entity, check ownership, assess risk, and screen for sanctions. Minor gaps exist, such as no explicit search/discovery tool or historical monitoring, but the primary lifecycle is complete.