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

With no annotations, the description fully discloses algorithm (merges fee-adjusted levels, walks the book), that it is a measurement not a prediction, assumptions (capital on each venue, no transfer costs), limitations (prices move), and the need for an API key. This provides deep behavioral insight beyond the basic function.

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 longer than average, but every sentence carries essential information: problem statement, algorithm, use cases, return values, parameter definitions, and caveats. It is logically front-loaded with the primary purpose and caveats placed at the end with the API key requirement. No filler or repetition.

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 complexity, multiple parameters, and the presence of an output schema, the description covers all needed contextual elements: parameter meanings, use-case instructions, behavioral limitations, authentication requirements, and return values. Even though an output schema exists, the description still summarizes what is returned, which improves 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?

Schema descriptions are absent (0% coverage). The description compensates by explaining each parameter: 'coin', 'notional_usd', 'side', and 'venues', including examples ('sol', 'binance,bybit') and the purpose of the venues param. Since schema provided no help, this is exemplary compensation.

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 opens with a specific, result-oriented statement: 'Cheapest way to fill a crypto perp order across multiple venues, and what that saves versus using the single best venue.' It clearly distinguishes the tool by its multi-venue routing and savings analysis, and names example queries. This separates it from generic order tools and the many sibling analysis tools.

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?

It gives explicit use cases ('Use for "how should I split this order"...'), and explains when the optional venues parameter matters. It warns that it is a static measurement, implying limitations for live execution, but it does not point to alternative sibling tools or explicitly state non-use conditions. Overall, the guidance is clear and context-aware.

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