US Stocks & Market Data

get_recommendations

Read-onlyIdempotent

[US Stock Info] Get recommendations or upgrades/downgrades for a given ticker symbol. You can also specify the number of months back to get upgrades/downgrades for, default is 12.

Args:
    ticker: str
        The ticker symbol of the stock to get recommendations for, e.g. "AAPL"
    recommendation_type: str
        The type of recommendation to get. You can choose from the following recommendation types: recommendations, upgrades_downgrades.
    months_back: int
        The number of months back to get upgrades/downgrades for, default is 12.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`ticker`	Yes
`months_back`	No
`recommendation_type`	Yes

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.3/5.0

Behavior3/5

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 a useful scoping detail: the default of 12 months for upgrades/downgrades. But it does not describe return format, pagination, or other behavioral nuances beyond what annotations and the output schema already imply.

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 well-structured with a brief introductory sentence followed by a clear Args list. Each parameter gets a concise line. It is slightly verbose due to repetition of 'upgrades/downgrades' and the use of type annotations, but overall it is efficient and scannable.

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?

The tool is simple, all parameters are documented, annotations cover safety characteristics, and an output schema exists. The description provides enough context for an agent to invoke the tool with correct arguments, and the output schema handles return-value expectations. Nothing essential is missing.

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?

The input schema has no descriptions (0% coverage), but the description fully compensates by explaining every parameter in detail. It provides an example ticker ('AAPL'), enumerates the allowed values for recommendation_type ('recommendations', 'upgrades_downgrades'), and specifies the default for months_back. This is a model of parameter documentation.

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's function: 'Get recommendations or upgrades/downgrades for a given ticker symbol.' It specifies the resource (stock ticker) and the exact kind of data (recommendations/upgrades/downgrades). This distinguishes it from sibling tools like get_finance_news or get_stock_info.

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 provides clear context for when to use the tool: whenever a user asks for stock recommendations or upgrades/downgrades for a specific ticker. It explains the optional 'months_back' parameter and its default, giving a practical usage scenario. However, it doesn't explicitly mention alternatives or when not to use this tool, so it falls short of a 5.

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

All US Stocks & Market Data tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.3/5.0

Disambiguation5/5

Each tool provides a distinct type of stock data: news, financial statements, historical prices, market overview, recommendations, and stock info. There is no functional overlap between them; the purpose of each is clear and mutually exclusive.

Naming Consistency5/5

All tool names follow the consistent get_ verb prefix followed by a descriptive resource, such as get_finance_news and get_historical_stock_prices. The naming pattern is uniform and predictable across the entire set.

Tool Count5/5

With six tools, the server is well-scoped for stock and market data retrieval. Each tool covers a major data category without unnecessary duplication, making the count appropriate and manageable.

Completeness4/5

The tool set covers key stock data needs including news, financial statements, historical prices, market overview, recommendations, and stock summaries. Missing features like direct quote or sector performance are minor and can be worked around with existing tools.

Resources

Need Help?