Returns analyst consensus for ETFs based on weighted average of holdings' ratings.
Args:
tickers: Comma-separated ETF tickers (e.g. 'QQQ,SPY,VTI')
| Name | Required | Description | Default |
|---|---|---|---|
| tickers | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint true, and destructiveHint false, establishing safety. The description adds meaningful context by explaining that the consensus is computed as a weighted average of holdings' ratings, which is a useful behavioral detail beyond the 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 concise, with two sentences plus an Args block. It front-loads the core purpose and gives an example without unnecessary detail. Every sentence earns its place.
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?
This is a low-complexity tool with one parameter and no output schema. The description covers the purpose, parameter format, and methodology, which is sufficient for basic usage. It does not describe the response format, but that gap is somewhat acceptable given the absence of an output schema.
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 provides no description for the 'tickers' parameter, so the description compensates by specifying 'comma-separated ETF tickers' with an example (QQQ,SPY,VTI). However, it only mentions the string form and omits the array alternative allowed by the schema, and does not specify any constraints like limits.
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 it returns analyst consensus for ETFs based on a weighted average of holdings' ratings, providing a specific verb, resource, and methodology. This distinguishes it from sibling ETF tools like get_etf_holdings or get_etf_exposures.
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 for ETF analyst consensus queries but does not explicitly mention alternatives or when not to use this tool. Differentiation from sibling tools is left to the user rather than being explicitly stated.
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.