get_company_procurementList the government procurement contracts a company has won (from open-contracting data): the awarding body, contract title, value and date. Strong signal of what a company actually does.
| Name | Required | Description | Default |
|---|---|---|---|
| country | Yes | ISO-2 country code, e.g. NG. | |
| registration_no | Yes | The registry number. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the data source ('open-contracting data') and the returned fields (awarding body, contract title, value, date), which is useful. However, it does not mention pagination, limits on results, or how missing contracts are handled, leaving gaps in behavioral transparency.
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 concise: two sentences that front-load the action and fields, then add a value proposition. Every sentence earns its place with no redundancy or filler.
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 list tool with two parameters and no output schema, the description provides enough context: it lists the key return fields and data source. However, it could be more complete by noting edge cases like companies with no contracts or geographic coverage, but overall it is sufficient for basic 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?
The input schema provides full descriptions for both parameters (country and registration_no) with 100% coverage. The description does not add any additional meaning about the parameters, so baseline 3 is appropriate.
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 specific verb 'List' and the resource 'government procurement contracts a company has won', with a data source and return fields. This distinguishes it from sibling tools like get_company and search_companies, which focus on company details or search rather than procurement contracts.
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 provides a clear use case: 'Strong signal of what a company actually does.' However, it does not explicitly state when not to use this tool or mention alternatives by name, though the sibling list implies context. It gives clear context but no exclusions or comparisons.
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.