outcomes_get_orderbook

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It only indicates 'read' via '[L:READ]' but omits details about rate limits, side effects, return format, or required permissions. For a tool with 3 parameters and no output schema, this is insufficient.

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 very short (two lines), but the use of cryptic tags like 'CAT:[预测]' and Chinese text '请先调用 agent_catalog' reduces clarity for an English-centric AI. It is front-loaded but at the expense of comprehensibility. Every character is present but not optimally informative.

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 has 3 parameters, no output schema, and no annotations, the description should provide more context about what an orderbook represents for prediction markets, how outcome and size interact, and what the return value looks like. The prerequisite 'agent_catalog' is mentioned but not explained. The description falls short of being complete.

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 baseline is 3. The description does not add any meaning beyond what the schema already provides for the three parameters (marketId, outcome, size). It fails to explain how outcome 'YES/NO' relates to prediction markets or how size affects the depth.

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 cryptic tags '[L:READ] CAT:[预测]' and a prerequisite note, but does not clearly state that the tool retrieves the orderbook for prediction outcomes. While the name is indicative, the description fails to differentiate from sibling tools like 'okx_get_orderbook', leaving ambiguity about the specific domain (prediction vs. spot/futures).

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 includes a prerequisite 'please call agent_catalog first', which provides some guidance on when to use this tool. However, it does not specify when to prefer this over alternatives like 'outcomes_get_ticker' or 'okx_get_orderbook', nor does it mention any exclusions. The guidance is minimal but not misleading.

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