screen_countryCheck whether a country or region carries sanctions designations
(OFAC-curated today). lists: optional comma-separated list slugs.
| Name | Required | Description | Default |
|---|---|---|---|
| lists | No | ||
| country | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds the context that the data is 'OFAC-curated today,' which hints at a specific data source and temporal limitation. Since annotations already declare readOnlyHint=true, the safety profile is covered. The description does not disclose further behavioral traits like result format or edge cases, but with the output schema present, this is sufficient.
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 exceptionally concise: two sentences that front-load the purpose and then add the key parameter detail. There is zero waste, and every word earns its place.
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 tool with two parameters and an output schema, the description covers the essential purpose and parameter usage. The note about OFAC curation conveys an important qualifier. With annotations and output schema present, the description is complete enough for an agent to use the tool correctly.
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 description explains the `lists` parameter as 'optional comma-separated list slugs,' adding value beyond the schema's generic string type. It does not explicitly describe `country`, but the parameter's purpose is clear from the tool's name and the description's main clause, so the description compensates well for the low 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's purpose: 'Check whether a country or region carries sanctions designations.' It uses a specific verb ('Check'), names the resource (country/region), and provides the domain (sanctions). This distinguishes it from sibling tools like screen_website or screen_email.
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 clear context for when to use this tool—when you need to check sanctions status for a country or region. It does not explicitly mention alternatives or exclusions, but the context is unambiguous, so it does not fall below a 4.
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 unique entity type: IP, country, crypto address, email, government ID, PEP, and website. The two IP-related tools (detect_vpn and geolocate_ip) are distinct in purpose and clearly named. No two tools overlap in what they screen.
The eight screen_* tools follow a consistent verb_noun pattern (e.g., screen_email, screen_website). The two IP tools (detect_vpn, geolocate_ip) use different verbs, creating minor inconsistency but still understandable given their unique actions.
With 8 tools, the server is well-scoped for a sanctions/anti-crime screening service. Each tool addresses a distinct screening domain, and the count is neither too thin nor bloated.
The tool set covers a wide range of entity types: IPs, countries, crypto, email, government IDs, PEPs, and websites. A minor gap exists for phone numbers or other entity types, but the primary screening workflows are well-covered and usable without workarounds.