US Stocks & Market Data

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds no extra behavioral context beyond the operation itself (e.g., no mention of rate limits or news source specifics), but it doesn't contradict the annotations. With annotations present, the bar is lower, and the description is adequate.

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

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

The description is extremely concise: a one-line purpose statement followed by a structured args section. No wasted words, and the parameter is clearly documented. The [US Stock Info] prefix adds light context without bloat.

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

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

With one simple parameter, existing output schema, and comprehensive annotations, the description is complete. It covers the tool's purpose and the parameter semantics, while the output schema handles return values. There is no significant missing information for an agent to correctly select and invoke this tool.

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

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

The input schema has zero description coverage for the parameter, but the description provides a full docstring: 'The ticker symbol of the stock to get news for, e.g. "AAPL".' This explains the semantic meaning and gives an example, fully compensating for the schema's lack of detail.

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

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 news for a given ticker symbol.' This is a specific verb+resource pair that distinguishes it from sibling tools like get_financial_statement or get_historical_stock_prices, which target different data types.

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

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

The description clearly implies the tool should be used when you need news for a specific ticker, as evidenced by the parameter requirement. It doesn't explicitly name alternatives or exclusions, but the context is unambiguous; an agent would know to use this for news retrieval versus other stock-related tools.

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

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

The annotations already cover the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), so the bar for behavioral disclosure is lower. The description adds useful context about the available financial statement types and parameter semantics, but it does not disclose edge-case behavior (e.g., invalid tickers, data currency, or time periods). This is acceptable but not comprehensive.

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

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

The description is reasonably well-structured with a purpose statement and an Args section, but it is repetitive: the list of financial statement types appears twice nearly verbatim (once in the overview and once in the financial_type explanation). This redundancy could be trimmed without losing meaning, making it slightly less concise than ideal.

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

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

The tool has only two parameters, both fully explained, and an output schema is present, so return values are documented elsewhere. The annotations cover side effects, and the '[US Stock Info]' prefix indicates the market scope. The description is largely complete, though it does not elaborate on the meaning or typical use of each financial statement type, which is a minor gap given the tool's purpose.

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

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

The schema provides zero description coverage (0%), leaving the description to fully explain the parameters. The description does this thoroughly: it defines 'ticker' with an example ('AAPL') and lists all six allowed values for 'financial_type' (income_stmt, quarterly_income_stmt, etc.). This fully compensates for the schema's lack of detail, giving the agent precise guidance on how to fill each argument.

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

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 financial statement for a given ticker symbol' and lists the specific financial statement types available. This distinguishes it from sibling tools like get_stock_info or get_finance_news, making the purpose unambiguous.

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

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 (to retrieve financial statements) and enumerates the available statement types, which helps an agent choose the appropriate variant (e.g., income_stmt vs. balance_sheet). However, it does not explicitly contrast with sibling tools or provide exclusionary guidance on when not to use it, so it lacks a small amount of directiveness.

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

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

Annotations already define this as readOnly, idempotent, and non-destructive, so the description doesn't need to repeat those. It adds the intraday 60-day limitation and default values, which are useful, but it does not disclose other behavioral aspects like data source, rate limits, or error conditions. The additional context is modest, so a mid-range score is appropriate.

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

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

The description is front-loaded with a clear purpose sentence and then structured as an Args list. It is concise and every section provides necessary detail without excessive verbosity. The only minor redundancy is listing the output fields, which may be covered by the output schema, but it still adds value.

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

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

For a read-only tool with an output schema, the description covers key invocation details: ticker example, period and interval valid values with defaults, and a critical data constraint. However, the unsupported 'start and end' mention and lack of error conditions or date format specifics leave some gaps. Overall, it is reasonably complete for typical use.

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

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

Given 0% schema description coverage, the description carries full responsibility for parameter meaning. It thoroughly documents ticker, period, and interval with valid values, defaults, and constraints. However, it references 'start and end' parameters that are not present in the schema, which could confuse an agent. Despite this flaw, it compensates well for the schema's lack of descriptions.

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

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

The description clearly states 'Get historical stock prices for a given ticker symbol' with a specific verb and resource. It lists the data fields returned, distinguishing it from sibling tools like news, statements, recommendations, or overview. The tool's purpose is unambiguous and specific.

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

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

The description gives clear context for when to use the tool (when historical stock prices are needed) and provides parameter usage instructions, including valid periods, intervals, and the constraint that intraday data cannot extend beyond 60 days. However, it does not explicitly mention alternatives or when not to use it, 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.

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

Annotations already declare read-only and idempotent hints, so the description doesn't need to restate those. It adds valuable behavioral context by disclosing that the tool reports whether the US regular session is open, and that a closed-market response refers to the last trading day's close.

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

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

The description is succinct, front-loaded with the US Stock Info tag, and every sentence adds value: components, usage guidance, no arguments, and the session-status behavior. No wasted words or redundancy.

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

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

For a no-parameter read-only market snapshot, the description fully covers what the tool returns, when to use it, and how to interpret the result (including session status). The presence of an output schema means return-value details are already structured elsewhere, so no additional explanation is needed.

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

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

The tool has zero parameters, and the description explicitly notes "Takes no arguments." The empty schema leaves nothing to explain, so the baseline of 4 for zero-parameter tools is upheld.

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

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

The description opens with "Get a snapshot of the overall US market" and enumerates the exact components (indices, VIX, yields, commodities, USD/KRW). It explicitly contrasts with single-company tools, making the tool's purpose and scope unmistakable.

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

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

It clearly states "Use this for questions about the market as a whole rather than a single company" and provides concrete example questions. It does not name specific alternative tools, but the contrast with single-company queries is explicit and sufficient for tool selection.

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

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.

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.

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.

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.

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.

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.

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description doesn't need to restate those. It adds context about the tool's scope (US stocks) and the summary nature of the data, but doesn't disclose potential edge behaviors such as handling of invalid tickers or rate limits. With annotations covering the safety profile, this is adequate.

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

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

The description is succinct and well-structured: a one-sentence function summary, a clear pointer to an alternative tool, and a formatted Args block. No redundant text; every sentence earns its place.

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

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

This is a simple single-parameter read-only tool with an output schema present. The description covers the purpose, the nature of the returned information, and the key alternative. Since the output schema exists, detailed return format documentation is not necessary.

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

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

The schema only defines ticker as a required string with no description. The description compensates by explaining 'The ticker symbol of the stock to get information for' and providing an example ('AAPL'), giving the parameter clear meaning beyond the schema's raw type.

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

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

Clearly states the tool's function: 'Get a summary of key information for a given ticker symbol' and enumerates specific data categories (price, market cap, ratios, dividend, etc.). It also explicitly contrasts with get_financial_statement for detailed statements, distinguishing its scope.

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

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

Provides an explicit recommendation to use get_financial_statement when detailed financial statements are needed. While it doesn't mention other sibling tools like get_finance_news or get_market_overview, the core use case and one key alternative are clearly stated.

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