TipRanks

get_all_forex_quotes

Read-onlyIdempotent

Real-time forex quotes: the most-traded pairs, each with a display name.

The feed carries 1,550 pairs in alphabetical order, which is far more than one
response can hold — so this returns the most prominent `limit` of them (majors
first, then by volume), and the response states how many were left out. Pass
`symbols` for specific pairs, or call get_forex_quote for a single one.

Read `note` before summarising: it says how many pairs the slice covers out of
how many exist, so a "top pairs" answer is not mistaken for the whole market.

`volume` on a forex row is a per-venue tick count, not market turnover — FX is
over-the-counter and most pairs report 0. It does not rank the market.

Args:
    symbols: Comma-separated pairs (optional; overrides the ranked slice)
    limit: How many ranked pairs to return (optional)

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	How many ranked pairs to return (default 40, max 75). Ignored when `symbols` is given.
`symbols`	No	Optional comma-separated pairs to return instead of the ranked slice, e.g. 'EURUSD,USDJPY'. Slash and dash forms are accepted.

TDQS

A4.9/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (readOnlyHint, idempotentHint, etc.), the description discloses crucial behavioral quirks: the feed has 1,550 pairs but returns a limited slice, the response states how many were left out, and 'volume on a forex row is a per-venue tick count, not market turnover... It does not rank the market.' This is significant context that annotations alone do not convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, then each paragraph addresses a distinct, necessary concern: the oversized feed and limit, the note field, the volume caveat, and parameter summaries. Every sentence earns its place—there is no filler or repetition of the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that there is no output schema, the description does a thorough job of explaining what to expect: a ranked slice, a note indicating coverage, and the caveat about volume. It also covers the main alternatives and data limitations, making it complete for an agent to decide when and how to call the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already provides full description coverage for both parameters, so the baseline is 3. The description adds value by explaining why `limit` exists (the feed exceeds response capacity) and how it interacts with `symbols` (symbols overrides the ranked slice), plus the significance of the `note` field in interpreting the result. This goes beyond the schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Real-time forex quotes: the most-traded pairs, each with a display name,' which clearly identifies the resource (forex quotes) and the specific scope (most-traded pairs, with display names). It distinguishes itself from sibling tools by explicitly mentioning 'call get_forex_quote for a single one' and by its focus on a ranked overview versus other asset-class quote tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance: 'Pass `symbols` for specific pairs, or call get_forex_quote for a single one.' It also explains when the ranked slice is appropriate versus using symbols, and warns to 'Read `note` before summarising' to avoid misrepresenting the data coverage. This effectively tells an agent when to use this tool and what to watch out for.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.8/5.0

Disambiguation3/5

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.

Naming Consistency4/5

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.

Tool Count1/5

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.

Completeness5/5

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.

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