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get_top_rated_stocks

Read-onlyIdempotent

Returns stocks most recommended by the best-performing analysts (by analyst track record).

Args:
    num: Number of results
    sector: Sector filter (financial, healthcare, technology, etc.) or empty for all
    country: 'US', 'Canada', 'UK', 'Global'. NOTE: UK tickers use GB: prefix but country param is 'UK'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
numNo
sectorNoLowercase sector filter: financial, healthcare, consumerdefensive, consumercyclical, utilities, materials, technology, industrials, energy, communicationservices, realestate (default: all sectors)
countryNo'US', 'Canada', 'UK', or 'Global' (default: US). UK tickers are returned with a 'GB:' prefix but the country value is still 'UK'.US

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is known. The description adds behavioral nuance: ranking by analyst track record and the UK ticker 'GB:' prefix quirk, which are not in the annotations. This goes beyond what structured fields provide.

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 starts with a clear purpose, then lists the three arguments with necessary details. Every line earns its place, including the important UK ticker note. It is slightly longer than necessary but remains efficient and well-structured.

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

Completeness4/5

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

For a simple read-only list tool with three parameters and no output schema, the description covers the purpose, ranking logic, and parameter nuances comprehensively. It does not specify the return fields, but that is often implicit for such a tool; overall it is complete enough for correct use.

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

Parameters3/5

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

Schema covers 67% of parameters with detailed descriptions for sector and country, including the UK prefix note. The description adds 'Number of results' for num, which the schema lacks, but mostly duplicates sector/country info. It adds some value but does not fully compensate for the uncovered num parameter.

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 the tool returns stocks recommended by top-performing analysts, using a specific ranking basis (analyst track record). It distinguishes itself from sibling tools like get_top_smart_score_stocks or get_best_performing_experts by identifying the selection criterion.

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

Usage Guidelines2/5

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

The description gives no explicit guidance on when to use this tool versus alternatives like get_top_smart_score_stocks or get_recent_analyst_ratings. It provides context (sector/country filters) but does not state when to choose this tool or when to avoid it.

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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