get_market_data

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

There are no annotations, so the description carries the full behavioral burden. It discloses that the tool fetches read-only market data and lists possible data types, but it does not mention time windows, response shape, pagination, authentication needs, or error behavior.

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 one efficient sentence with a front-loaded action verb and useful examples. Every part contributes to understanding the tool, with no filler 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?

The tool is simple with a single parameter, but there is no output schema and no annotation context. The description names return categories but leaves the actual response format, time range, and edge-case behavior implicit, which is a notable gap for a tool an agent must invoke and interpret.

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, so the description must compensate. It clarifies that 'symbol' is the identifier for which market data is fetched, but it provides no format, example value, or additional constraints beyond the schema's 'symbol' string property.

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 uses a specific verb ('fetches') and resource ('recent market data for a symbol'), with concrete examples of what counts as market data: quotes, candles, or latest trades. This clearly distinguishes it from sibling tools like list_symbols or get_symbol, which focus on instrument metadata rather than live market data.

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?

No guidance is provided about when to prefer this tool over alternatives or what conditions make it appropriate. The description implies it is for market data retrieval, but it never explicitly compares against sibling tools or states exclusions.

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