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

With no annotations provided, the description carries the full disclosure burden. 'Fetch' correctly signals a read-only operation, and 'bids and asks' hints at the response shape. However, it omits details such as whether the data is a live snapshot, how levels are aggregated, or any exchange-specific quirks. For a simple read tool this is adequate but not rich.

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, front-loaded sentence that states the action and the resource with zero filler. Every word contributes to understanding the tool's purpose.

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 description covers the core purpose, and the schema fully documents the parameters and constraints. Although there is no output schema, the phrase 'bids and asks' conveys the essential return structure. Missing details like price/quantity field ordering are minor for this simple read tool.

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 description coverage is 100%, so the schema already documents each parameter with types, defaults, constraints, and an exchange whitelist. The description adds no parameter-specific meaning, which is acceptable since the schema carries the full semantic load.

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 the specific verb 'Fetch' and names a concrete resource: 'order book depth (bids and asks)' for a trading pair. This clearly distinguishes it from sibling tools like get_ticker, get_trades, and get_ohlcv, which all target different market data dimensions.

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 the tool is for liquidity/depth data, but it does not explicitly state when to prefer it over alternatives or exclude other data types. An agent can infer the use case from the phrase 'order book depth', but no direct comparison to sibling tools is provided.

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