Peer/competitor companies for a stock, with comparative metrics for side-by-side analysis. Read-only, no side effects.
Use to find and compare a company against similar names (competitors,
same-sector peers). For that company's own data use get_assets_data; for a
sector-wide breakdown use get_sector_analysis.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker | Yes | Stock ticker symbol, e.g. 'AAPL'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well covered. The description adds that the tool provides 'comparative metrics for side-by-side analysis' and explicitly states 'Read-only, no side effects,' which reinforces but does not significantly expand beyond the annotations. The added context about the output purpose is useful, but there is minor redundancy.
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 main purpose and followed by usage guidance. It is concise with no filler or wasted words, efficiently conveying the tool's function and boundaries.
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 simple tool with one parameter, strong annotations, and no output schema, the description provides adequate context: it explains what the tool returns (comparative metrics), when to use it, and how it differs from alternatives. No critical information is missing for an agent to decide invocation.
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 description coverage is 100%, with the ticker parameter described as 'Stock ticker symbol, e.g. 'AAPL'.' The description does not add any further explanation about the parameter beyond the schema, so the baseline of 3 is appropriate.
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 identifies 'peer/competitor companies for a stock, with comparative metrics for side-by-side analysis.' It uses a specific verb (find/compare) and resource (peer companies) and distinguishes from siblings by noting alternatives for own data (get_assets_data) and sector-wide analysis (get_sector_analysis).
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 explicitly says when to use the tool: 'Use to find and compare a company against similar names (competitors, same-sector peers).' It also provides clear exclusions: 'For that company's own data use get_assets_data; for a sector-wide breakdown use get_sector_analysis.' This names alternatives and scenarios.
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.