Returns market-wide performance for a specific country: average returns, sector breakdown, top/bottom performers.
Args:
country: Country code: 'us', 'ca', 'gb', 'de', 'il', 'au', 'hk', 'sg', etc.
| Name | Required | Description | Default |
|---|---|---|---|
| country | No | us |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds context about the output contents (sector breakdown, top/bottom performers) but no additional behavioral traits like data freshness, pagination, or any side effects. It does not contradict annotations.
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 sentences, front-loaded with the core purpose and then the parameter. Every word earns its place; no filler or redundant restating of the tool name or annotations.
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?
With a single optional parameter, rich annotations, and no output schema, the description covers the essential purpose and parameter semantics. However, it omits details like whether data is real-time or historical, and the country list is open-ended ('etc.'), which could leave edge cases unclear. Still, for a read-only simple lookup, it is largely complete.
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 only provides a title 'Country' with a default, and schema description coverage is 0%. The description compensates by explaining the country parameter with explicit examples ('us', 'ca', 'gb', etc.), adding meaningful guidance beyond the raw schema. The 'etc.' leaves some ambiguity, but it is sufficient for the common cases.
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 market-wide performance for a specific country, enumerating the exact data included (average returns, sector breakdown, top/bottom performers). This distinguishes it from sibling tools like get_market_movers or get_sector_analysis by explicitly scoping to country-level market performance.
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 usage when country-level market performance is needed, but it does not explicitly contrast with alternatives such as get_market_movers, get_sector_analysis, or get_market_commentary. It lacks clear when-to-use or when-not-to-use guidance.
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.
Many tools have overlapping purposes, e.g. get_etf_analysis vs get_etf_forecast both provide ETF analyst consensus, get_etf_holdings vs get_etf_top_stocks both list constituents, and get_portfolio_overview vs get_portfolio_performance both return returns/performance. The detailed descriptions help, but the sheer number of similar tools creates ambiguity in selection.
The set is largely consistent with a 'get_' prefix and descriptive nouns (get_stock_quotes, get_crypto_quote, get_dividend_history). Minor deviations include 'list_my_portfolios' instead of 'get_my_portfolios' and singular/plural variants like get_all_commodities_quotes vs get_commodity_quote, but the pattern remains predictable.
With 71 tools, the count far exceeds the 50+ threshold described as an extreme mismatch. Even though the server covers a broad financial domain, such a large surface is overwhelming for an agent and includes many redundant or highly specific tools that could be consolidated.
The tool set provides comprehensive coverage of TipRanks data: quotes and historical data for all major asset classes, news, earnings and economic calendars, analyst and sentiment data, financial statements, technical analysis, options, portfolios, and screeners. There are no obvious dead ends for typical financial research tasks.