Current government yield curve for an African country — latest T-bill/bond auction per tenor with stop rates and yields. 13 countries covered.
| Name | Required | Description | Default |
|---|---|---|---|
| country | Yes | ISO-2 country code, e.g. NG, KE, GH. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful context about data freshness ('latest auction per tenor') and coverage ('13 countries covered'), but it does not elaborate on return format, pagination, or potential errors. This is consistent with annotations and provides moderate added 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 two concise sentences, front-loaded with the primary purpose and immediately followed by a key limitation. Every word adds value, 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 single-parameter read-only tool, the description covers the essential information: what data is returned (yield curve, auctions, stop rates, yields) and the coverage limit (13 countries). While it doesn't specify the exact response structure, the tool's simplicity and schema coverage make this sufficient.
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 schema fully describes the 'country' parameter with ISO-2 code examples, achieving 100% schema coverage. The description adds little beyond reinforcing that it covers African countries, so the baseline of 3 is appropriate given the schema already handles parameter semantics.
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 returns the current government yield curve for African countries, specifically mentioning T-bill/bond auctions per tenor with stop rates and yields. This specific verb-resource combination distinguishes it from sibling tools like get_african_policy_rates or get_african_fx_rates.
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 the tool is for yield curve data and notes the 13-country coverage limitation, but it does not explicitly state when to use this tool over alternatives or provide any exclusion criteria. The usage context is implied rather than explicitly guided.
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.
Tools are largely distinct in purpose, with clear resource-specific patterns like get_african_exchange_stocks vs get_ngx_all_stocks. Some overlap exists between generic African tools and NGX-specific convenience wrappers (e.g., get_market_open_status vs get_ngx_market_status), and get_african_policy_rates overlaps with get_country_macro_indicators on inflation/policy rate data, but descriptions clarify these boundaries.
All tools follow a consistent get_<domain>_<object> snake_case pattern, with plural/singular used appropriately (e.g., get_african_exchanges vs get_african_exchange). No mixed conventions or vague generic verbs—every name clearly signals its resource.
At 21 tools, the server is on the heavier side but within the 16-25 borderline zone. Each tool addresses a distinct data need for the broad African-markets domain, though some redundancy from NGX-specific wrappers (e.g., get_ngx_market_status vs get_market_open_status) could be trimmed.
The server covers a wide range of market data: exchanges, indices, stocks, FX, macro indicators, yield curves, and bank data. Minor gaps include lack of single-stock price/history for non-NGX exchanges and limited historical data beyond Nigeria's macro series, but core market-analysis workflows are well supported.
