get_intraday_prices

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions what data is retrieved but doesn't cover critical aspects like rate limits, authentication needs, error handling, or the format of returned data (though an output schema exists). The description is minimal and lacks behavioral context beyond the basic operation.

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 highly concise and well-structured: a brief purpose statement followed by a clear, bullet-like parameter explanation. Every sentence earns its place by adding essential information without redundancy, making it easy to scan and understand.

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?

Given the tool's moderate complexity (3 parameters, no annotations, but with an output schema), the description is partially complete. It covers parameter semantics effectively but lacks usage guidelines and behavioral transparency. The presence of an output schema reduces the need to explain return values, but more context on tool behavior and differentiation would improve completeness.

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 description adds significant value beyond the input schema, which has 0% description coverage. It explains each parameter's purpose (e.g., 'Stock symbol', 'Time frame', 'outputsize' with meanings like 'compact' for last 100 data points), clarifying semantics that the schema's titles and enums alone don't provide. This 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 the tool's purpose as 'Get intraday price data' with a specific verb ('Get') and resource ('intraday price data'), distinguishing it from sibling tools like 'get_daily_prices' and 'get_technical_indicators'. However, it doesn't explicitly differentiate from 'get_daily_prices' beyond the 'intraday' qualifier, which is implied but not contrasted.

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 no guidance on when to use this tool versus alternatives like 'get_daily_prices' or 'get_technical_indicators'. It lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage based on the tool name alone.

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