Last quote

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

The annotations already declare readOnlyHint=true and openWorldHint=true, indicating safe read behavior. The description adds value by specifying exactly what is returned (best bid/ask with sizes), which goes beyond the annotations and clarifies the output content. There is no contradiction.

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 a single sentence that front-loads the core purpose. Every word is meaningful and no unnecessary information is included. It is concise and well-structured.

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 presence of an output schema (not shown but indicated) and the simple input with 100% coverage, the description is complete. It adequately covers the tool's function without needing additional details about return values or behaviors beyond what's in the schema and annotations.

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?

Schema coverage is 100%, with detailed descriptions for both parameters (venue types, symbol examples). The description adds minimal new semantic information beyond 'for a symbol on a venue.' The schema already does the heavy lifting, so a baseline score of 3 is appropriate.

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 returns the top-of-book quote (best bid/ask with sizes) for a symbol on a venue. It uses a specific verb and resource, and the phrase 'top-of-book quote' distinguishes it from sibling tools like last_trade (last trade price) or crypto_bars (historical bars).

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 implies usage context: if you need the current best bid/ask with sizes for a symbol on a venue, use this tool. However, it does not explicitly state when not to use it or mention alternative tools for similar but different data (e.g., last_trade for last trade price).

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