Returns asset allocation by type/country/top stocks and distribution by sector, market cap, dividend yield, beta, and P/E.
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, openWorldHint, idempotentHint, and non-destructive, so the safety profile is disclosed. The description adds the behavioral fact that portfolio_id must be obtained from list_my_portfolios, which is useful but not a major new behavioral trait. No contradictions exist.
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 compact and front-loaded with a comprehensive list of output dimensions in one sentence, followed by an Args block. Every sentence earns its place; there is 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 read-only analysis tool with one parameter and no output schema, this description is complete. It explains what to expect (allocation/distribution data) and how to satisfy the input (portfolio_id from list_my_portfolios). No major gaps remain.
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 0% for portfolio_id, so the description must compensate. It explicitly connects the parameter to list_my_portfolios, giving the agent a clear way to obtain valid IDs. This is valuable semantic context that the schema alone lacks, though it doesn't cover additional formats or constraints.
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 the specific verb 'Returns' and clearly enumerates the resource: asset allocation by type/country/top stocks and distribution by sector, market cap, dividend yield, beta, and P/E. This distinguishes it from sibling portfolio tools like get_portfolio_holdings or get_portfolio_overview by specifying the exact analytical content.
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 provides clear context about when to use this tool: when you need allocation and distribution metrics for a portfolio. It also gives a crucial prerequisite—portfolio_id must come from list_my_portfolios. However, it does not explicitly contrast with alternatives or state when not to use it, so it misses the full 5.
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.