get_position_book

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

The description explains key behaviors beyond the readOnlyHint annotation: the return shape (time, price, bucketWidth, buckets), the meaning of longCountPercent/shortCountPercent as decimal strings representing percentages, and the trimming of buckets to at most depth on each side of the current price. This gives the agent a clear understanding of what to expect without relying on the output schema.

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 well-structured: an opening sentence stating the purpose, followed by a clarifying sentence about the relationship to the order book, and a detailed but concise enumeration of the return fields. Every sentence adds value and the content is front-loaded with the main action.

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 moderate complexity and the presence of a full input schema plus an output schema, the description provides all necessary context: the purpose, the distinction from order book, the field semantics, and the depth trimming behavior. It is complete enough for an agent to select and invoke the tool correctly without needing additional external knowledge.

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?

While the input schema already covers all three parameters with descriptions, the tool description adds semantic nuance: it explains that percent values are decimal strings (e.g., '"0.2543" means 0.2543%'), and that the buckets are trimmed to 'at most depth buckets on each side of the current price.' This enriches the schema's baseline and helps the agent interpret parameter behavior correctly.

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 verb and resource: 'Fetch the aggregate open-position book for an instrument.' It clearly distinguishes itself from the sibling get_order_book by explicitly noting that this is about open positions rather than pending orders, with the same shape but different semantics.

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 when to use this tool by contrasting it with the order book ('Same shape as the order book, but each bucket's longCountPercent/shortCountPercent describe open positions... rather than pending orders'). It does not explicitly name an alternative, but the context makes it clear that position data is the focus, differentiating it from order-related tools.

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