Returns the real-time price quote for a specific commodity.
Common symbols: GCUSD (gold), SIUSD (silver), CLUSD (crude oil),
NGUSD (natural gas), HGUSD (copper), PLUSD (platinum).
Args:
symbol: Commodity symbol (e.g. 'GCUSD' for gold)
| Name | Required | Description | Default |
|---|---|---|---|
| symbol | Yes | Commodity symbol, e.g. 'GCUSD' (gold), 'CLUSD' (crude oil). |
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 context about real-time data and lists common symbols, but it doesn't disclose potential latency, data source, or error behavior for invalid symbols. This is adequate but not rich given the annotation coverage.
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 concise sentences plus an Args line. It is front-loaded with the primary purpose, followed by the symbol list. Every sentence serves a purpose with 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?
Given the tool's simplicity (one parameter, no nested objects), the description covers the essential purpose, input, and scope. With good annotations and no output schema, the lack of return-value details is acceptable for a quote tool. The only notable gap is explicit mention of alternatives, but the context is otherwise 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 input schema provides a description with two examples, and the description expands on this with a list of six common symbols (GCUSD, SIUSD, CLUSD, etc.), which is helpful for selecting valid inputs. Since schema coverage is 100%, the added symbol list is a meaningful enrichment beyond the schema.
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 'Returns the real-time price quote for a specific commodity' with a specific verb, resource, and scope. It distinguishes from siblings like get_all_commodities_quotes (all vs. specific) and get_commodity_historical (real-time vs. historical) by explicitly qualifying 'specific commodity' and 'real-time'.
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?
Usage is implied by the phrase 'specific commodity' and the provided symbol list, but there is no explicit guidance on when to use this over get_all_commodities_quotes or get_commodity_historical. No alternatives are mentioned, so the agent must infer the appropriate context from the name and description.
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.