list_banksList every bank and financial institution held for a country, with its bank code, SWIFT/BIC, USSD shortcode and mobile-money flag. Use this to build a bank picker or to reconcile a list of institutions.
| Name | Required | Description | Default |
|---|---|---|---|
| country | Yes | ISO-2 country code, e.g. NG, GH, KE, ZA, EG, MA, ZM, TZ. | |
| mobile_money_only | No | Return only mobile-money providers (default false). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the transparency burden. It discloses the return fields (bank code, SWIFT/BIC, USSD shortcode, mobile-money flag) and the country scope. It could mention pagination or ordering, but for a simple list tool this is sufficiently transparent.
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?
Two sentences: the first front-loads the operation and output fields, the second provides a concise use-case note. Every word earns its place; there is no repetition of schema information.
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 explains what the tool returns, why to use it, and the country scoping. Since the schema documents parameters and there is no output schema, the description adequately covers the essentials for a simple list tool.
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% for both parameters, including an ISO-2 country example and a default for mobile_money_only. The description adds use-case context but no parameter-specific syntax beyond what the schema already provides, so a baseline of 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 is specific: it lists every bank and financial institution for a country, with named output attributes. The verb 'list' and scope 'every bank' clearly distinguish it from the sibling 'lookup_bank', which implies a single-bank lookup.
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 gives explicit use cases: 'build a bank picker' or 'reconcile a list of institutions'. It does not explicitly state when not to use it or name alternatives, but the 'list' vs 'lookup' distinction among siblings provides adequate contextual guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool targets a distinct data type: currency, holidays, banks (list vs lookup), phone network, and NUBAN account resolution. Even the two bank tools are clearly separated by purpose—listing all institutions vs resolving one from an identifier. No tool overlaps meaningfully with another.
All tool names follow a uniform verb_noun snake_case pattern (get_, list_, lookup_, resolve_), making the action and resource immediately clear. The convention is applied consistently across all six tools.
With six tools, the server sits comfortably in the ideal 3-15 range. Each tool covers a distinct reference data need without bloat or redundancy, making the count well-scoped for the stated purpose.
The set covers core African financial reference data—currencies, holidays, banks, mobile networks, and NUBAN validation. However, there is no tool to list supported countries or all currencies, which would be a natural complement to the country-based lookups. This is a minor gap that agents can work around.