List a company officers (name, position, start / end dates, current flag) by jurisdiction + company number via OpenCorporates. Read-only; price 0.0 (free).
| Name | Required | Description | Default |
|---|---|---|---|
| jurisdiction | Yes | Jurisdiction code (e.g. gb, us_de) | |
| companyNumber | Yes | Registry company number |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It states 'Read-only' and price 0.0, which is useful. However, it omits details like rate limits, pagination, or error handling. The read-only hint is helpful but incomplete for a full behavioral picture.
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 with a parenthetical list of output fields. It is concise, front-loaded, and contains no redundant information. Every word adds value.
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 listing tool with 2 parameters and no output schema, the description covers purpose, input, output fields, source, and cost/read-only status. Missing details like pagination or response structure are minor gaps; the listed output fields partly compensate for the lack of output schema.
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 descriptions for both parameters. The description mentions 'by jurisdiction + company number', matching the schema but adding no extra semantics such as format examples or allowed values. Baseline 3 is appropriate given full schema coverage.
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 lists company officers, specifies output fields (name, position, dates, current flag), and required inputs (jurisdiction + company number). It names the data source (OpenCorporates) and is distinct from sibling tools like company_registry_company_profile (profile) or company_registry_search_company (search).
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 notes it is read-only and free, which helps usage decisions. However, it does not explicitly state when to use vs. alternatives like company_registry_company_profile for detailed company info or when not to use (e.g., no company number). The sibling tools' purposes are different, so the context is reasonably clear.
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.
Most tools are clearly distinguished by domain prefixes (e.g., bid_watch, grant_watch) and specific action verbs. However, the high number of similarly structured watch tools could still cause confusion, though descriptions clarify exact purposes.
Every tool follows a consistent `domain_subdomain_action` pattern with underscores, e.g., `agent_audit_query`, `bid_watch_search`. Even long names like `commerce_catalog_agent_readiness_score` adhere to this structure.
With 147 tools, the server is far too broad, covering weather, carbon estimates, domain intel, and more—well beyond its stated 'Japan public-data ledgers' scope. This sheer volume overwhelms agents and dilutes focus.
The server offers many read-only tools for Japanese public data (bids, grants, licenses, etc.), but lacks create/update/delete operations for those domains. Additionally, numerous unrelated tools (e.g., carbon estimates, weather) feel tacked on, leaving gaps in core coverage.