TipRanks

get_economic_calendar

Read-onlyIdempotent

Returns upcoming and recent economic events (Fed meetings, jobs reports, CPI, GDP).

Defaults to US events at High/Medium impact only because the raw feed includes
hundreds of low-impact items from every country.

Args:
    daysBack: Days to look back (default 0)
    daysForward: Days to look forward (default 7)
    fromDate: Start date ISO format (alternative to daysBack)
    toDate: End date ISO format (alternative to daysForward)
    countries: Comma-separated country names to keep (default 'US').
               Pass an empty string to disable the country filter.
               Common values: 'US','UK','Germany','Japan','China','Canada','France'.
    impact: Comma-separated impact levels to keep (default 'High,Medium').
            Valid values: 'High','Medium','Low'. Pass empty to keep all levels.
    limit: Max events returned after filtering (default 50, max 200).

Returns: { totalMatched, returned, filters, economicCalendar: [...] }.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No
`impact`	No	Comma-separated impact levels to keep: High, Medium, Low (default 'High,Medium'); pass '' to keep all.	High,Medium
`toDate`	No
`daysBack`	No
`fromDate`	No
`countries`	No	Comma-separated country names to keep (default 'US'); pass '' to keep all. Examples: 'US','UK','Germany','Japan','China'.	US
`daysForward`	No

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context by explaining why default filters exist and how the raw feed is noisy, helping agents understand the need to adjust filters for broader results. No contradictions with annotations.

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?

Well-structured with a one-sentence purpose, a concise rationale, a clean Args list, and a Returns line. Every line is informative and there is no fluff or repetition of schema fields.

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?

Despite having 7 parameters and no output schema, the description covers all parameters, defaults, filter behavior, and the return shape ({ totalMatched, returned, filters, economicCalendar }). It provides enough information for an agent to call the tool correctly without additional documentation.

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

Parameters5/5

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

Schema coverage is only 29%, but the description thoroughly documents all 7 parameters, including defaults, valid values, and the alternative relationships between daysBack/fromDate and daysForward/toDate. This fully compensates for the schema gaps and goes beyond basic definitions.

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 uses a specific verb ('Returns') and resource ('economic events') with concrete examples (Fed meetings, jobs reports, CPI, GDP), clearly distinguishing it from sibling tools like earnings or IPO calendars.

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

Usage Guidelines4/5

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

The description explains default behavior ('Defaults to US events at High/Medium impact only') and the rationale (raw feed includes hundreds of low-impact items), providing clear context for when to use the tool. However, it does not explicitly mention when not to use it or point to alternatives, so it misses the highest bar.

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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