Returns lifetime / 1mo / 6mo / 12mo / YTD returns, Sharpe ratio, and a monthly-return time series. The monthly history field is chart-ready — a list of {month, return} points suitable for direct plotting.
Args:
portfolio_id: One of the IDs returned by list_my_portfolios.
| Name | Required | Description | Default |
|---|---|---|---|
| portfolio_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, covering the safety profile. The description adds meaningful behavioral detail by specifying the exact output fields and noting that the monthly history is chart-ready as a list of {month, return} objects, which goes 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?
The description is concise and structured: it first summarizes the returned metrics, then clarifies the shape of the monthly history field, and finally documents the parameter. Every sentence contributes useful information with no filler or repetition.
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 read-only tool with a single parameter and no output schema, the description covers the main return values and the parameter source. Minor gaps remain, such as units for returns and possible error behavior for invalid IDs, but the overall context 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 schema only defines portfolio_id as an integer with no supporting description (0% coverage). The description compensates well by explaining that the ID must be one returned by list_my_portfolios, giving the agent a concrete source for valid values.
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 that the tool returns a portfolio overview with specific metrics (returns for multiple periods, Sharpe ratio, and a monthly-return time series). However, it does not explicitly differentiate itself from the similar sibling tool get_portfolio_performance, so it misses the highest bar for sibling distinction.
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 a useful prerequisite by saying portfolio_id must be one of the IDs returned by list_my_portfolios, but it does not explain when to choose this tool over alternatives like get_portfolio_performance or get_portfolio_analysis. Usage context is implied rather than explicit.
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.