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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: it explains the aggregation logic (merged across venues, aggregated by exact price), the plan-based level limits (free=5, Starter=10, Pro=25), and explicitly states 'Descriptive market data only' to prevent misuse. This goes beyond what annotations provide.

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 compact and front-loaded: it states the core function in the first sentence, gives example queries, then covers plan limits and the read-only nature. Every sentence earns its place, and the structure flows logically from what → when → constraints.

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 tool has an output schema, so return values are already documented. The description covers the key contextual gaps: aggregation behavior, plan-based level limits, and the read-only nature. It could mention pagination or the exact structure of the top levels, but the output schema likely covers that, and the description is sufficient for an agent to select and invoke the tool correctly.

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 all three parameters (coin, pair, levels) with their defaults and constraints. The description adds the plan-based level ceiling context, which complements the schema's 'hard' ceiling note, but does not substantially add meaning beyond the schema. Baseline 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 states a specific verb ('merged', 'aggregated') and resource ('order book for one pair'), and distinguishes it from siblings by emphasizing the merged/aggregated nature across streamed venues. It also gives concrete example queries ('where are the walls on BTC', 'how deep is the bid', 'what is the spread'), making the tool's purpose unmistakable.

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 clear context for when to use the tool via example questions, and implicitly distinguishes it from other market data tools by focusing on order book depth and spread. It does not explicitly name alternative tools or state when not to use it, but the examples and 'Descriptive market data only' caveat give adequate guidance.

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