get_stock_market_cap

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 states the tool retrieves data (implying read-only) and shows an example return format, but doesn't mention rate limits, authentication requirements, data freshness, error conditions, or whether the date range is inclusive/exclusive. The example helps but leaves many behavioral aspects unspecified.

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 clear sections (Args, Returns) and uses an example effectively. It's appropriately sized for a 3-parameter tool with no annotations. The only minor inefficiency is repeating the tool name in the example call when it's already clear from context.

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 data retrieval tool with 3 parameters and no annotations, the description provides good coverage: clear purpose, full parameter documentation, and example output format. The main gap is lack of usage guidance relative to sibling tools. Without an output schema, the example return format is particularly valuable.

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?

With 0% schema description coverage, the description fully compensates by providing detailed parameter documentation. It clearly explains all three parameters (fromdate, todate, ticker) with their purposes, formats (YYYYMMDD for dates), and includes a concrete example showing valid values. This adds substantial meaning beyond the bare schema.

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 with a specific verb ('Retrieves') and resource ('market capitalization data for a specific stock'), distinguishing it from siblings like get_stock_fundamental or get_stock_ohlcv which retrieve different types of financial 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like get_stock_fundamental or get_stock_ohlcv, nor does it explain what makes market capitalization data unique or when it's preferred over other financial metrics.

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