Get the latest 200 corporate disclosures and regulatory announcements from NGX-listed companies — earnings, dividends, board changes, and filings.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds a concrete behavioral detail: the fixed 200-item limit and the types of content included. This is useful context beyond what annotations provide.
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?
A single sentence, front-loaded with 'Get the latest 200', clearly structured with a dash listing content categories. There is no fluff, and 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 parameterless read-only tool with safety annotations, the description fully specifies the purpose, scope, limit, and content types. No output schema exists, but the description is sufficient for an agent to select and invoke 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 tool has zero parameters, so the input schema is complete at 100% coverage. The description correctly avoids inventing parameters. Baseline 4 applies for parameterless tools since there is nothing to explain.
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 uses a specific verb 'Get' and resource 'corporate disclosures and regulatory announcements' with clear scope 'NGX-listed companies' and enumerates content types (earnings, dividends, board changes, filings). This clearly distinguishes it from sibling market-data tools like get_ngx_stock_price or get_ngx_top_gainers.
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?
No explicit alternatives are named, but the description clearly defines a niche: corporate disclosures vs. market data. Sibling tools all focus on market statistics, so the context is obvious. The 'latest 200' provides a clear usage expectation, though it lacks an explicit when-not-to-use statement.
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.
