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TipRanks

by com.tipranks

get_bulls_bears_summary

Read-onlyIdempotent

Returns the discrete bull and bear key points for stocks — the individual sentence bullets TipRanks shows on its stock pages, each tagged with a topic.

Args:
    tickers: Comma-separated tickers (e.g. 'AAPL,TSLA')

Returns JSON: {"data": [...one entry per ticker...]}. Each entry has:
  - ticker, updatedOn
  - bullish: list of bullish point sentences
  - bearish: list of bearish point sentences
  - key_points: list of {sentiment, topic, point} for the full set.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickersYes

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds behavioral context by explaining the discrete sentence-bullet format and the exact JSON return structure (ticker, updatedOn, bullish, bearish, key_points). It does not discuss auth/rate limits, but for a read-only list tool with these annotations, this is adequate and adds value beyond annotations.

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

Conciseness4/5

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

The description is structured with sections for Args and Returns, using bullet-like formatting for clarity. It is longer than the TDQS high bar but still efficient; the returns section is lengthy but necessary since there is no output schema. No redundant fluff, though the opening sentence is slightly verbose.

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?

Since there is no output schema, the description carries full burden for return values and does so thoroughly: it gives the JSON structure, per-ticker fields, and the nested key_points with sentiment/topic/point. It also covers the parameter format. For a read-only data retrieval tool, this is complete enough for an agent to invoke and parse the result.

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 input schema has 0% parameter description coverage, so the description must compensate. It explains the tickers arg as 'Comma-separated tickers (e.g. 'AAPL,TSLA')', giving a concrete format and example. However, it does not mention that an array is also accepted per the schema, which is a minor gap but still adds substantial meaning.

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 clearly states it returns 'the discrete bull and bear key points for stocks' with a specific resource (TipRanks stock pages) and detailed output structure. This distinguishes it from sibling tools like get_ai_stock_analysis or get_stock_quotes, which serve different purposes.

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

Usage Guidelines3/5

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

The description implies usage (when you need bull/bear key points for stocks) but gives no explicit when-to-use vs alternatives, no exclusions, and no mention of preferred contexts. It is not misleading, but guidance is only implicit.

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.

Resources