outcomes_get_candles

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

With no annotations provided, the description carries full burden for behavioral disclosure. The '[L:READ]' tag hints at read-only behavior, but no details about authentication, rate limits, or side effects are given. Minimal transparency.

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 extremely short but lacks essential information. It is not well-structured for an AI agent; it includes a prerequisite call but does not explain the tool's own function. Under-specification rather than proper conciseness.

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 4 parameters, 2 required, no output schema, and no annotations, the description is completely inadequate. It fails to explain return format, how results relate to sibling tools like okx_get_candles, or the prediction market context. Cannot effectively guide agent invocation.

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 all parameters (bar, limit, outcome, marketId) have descriptions in the schema. The tool description adds no additional semantic meaning beyond what the schema already provides. 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 is vague; it only contains '[L:READ] CAT:[预测]' and a reference to calling agent_catalog. It does not explicitly state that the tool retrieves candlestick data for prediction market outcomes. The purpose is implied by the tool name but not clarified by the description.

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?

No guidance on when to use this tool versus alternatives like okx_get_candles or okx_predictions_candles. The only directive is to call agent_catalog first, which is a prerequisite, not a usage condition.

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