get_stock_quote

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 provides 'real-time' quotes, which is useful context, but doesn't cover other important aspects like rate limits, data sources, error handling, or what the output looks like (e.g., price, volume, timestamp). For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 extremely concise and front-loaded, with every sentence earning its place. The first sentence states the core purpose, and the second provides essential examples without unnecessary details. There's zero waste, making it easy to parse quickly.

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 complexity of financial data tools, no annotations, and no output schema, the description is incomplete. It lacks information on return values (e.g., what fields are included in the quote), error cases, authentication needs, or performance characteristics. While concise, it doesn't provide enough context for reliable use without additional assumptions.

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 100% description coverage, with the 'symbol' parameter clearly documented. The description adds value by providing concrete examples (e.g., 'AAPL', 'RELIANCE.NS') and clarifying regional distinctions (US vs. Indian NSE stocks), which helps users understand valid inputs beyond the schema's generic description. However, it doesn't explain parameter constraints or formats in depth.

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 ('Get') and resource ('real-time stock quote'), making it immediately understandable. However, it doesn't explicitly distinguish this tool from its siblings (like 'get_crypto_price' or 'get_top_movers'), which would require mentioning it's specifically for stocks rather than other asset classes.

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 lists example symbols but doesn't explain why to choose this over sibling tools like 'get_crypto_price' for cryptocurrencies or 'get_top_movers' for market trends. There's no mention of prerequisites, limitations, or comparative context.

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