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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds meaningful behavioral details beyond this: the outcome IS NULL condition, the 'returns most recent first' caveat, and the demonstration of real-time publishing. No contradiction with annotations is present.

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 well-structured and front-loaded with the purpose, followed by triggers, when-to-call, prerequisites, next steps, caveats, and args. While the trigger examples and explanatory sentences are somewhat verbose, each section is purposeful and earned.

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 simplicity (2 optional parameters) and the presence of an output schema, the description covers all necessary context: prerequisites, next steps, caveats, parameter semantics, and usage triggers. It is complete for an agent to decide when and how to invoke it.

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?

Despite 0% schema description coverage, the description fully compensates by explaining target_market as an optional filter with allowed values (coin_market, kr_market, us_market), and limit as a maximum with a default of 20. This adds clear meaning beyond the bare schema types.

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 'Purpose' line explicitly defines the tool's function: returns currently pending predictions (outcome IS NULL), and the 'When to call' section clarifies its role in verifying ongoing prediction activity. This clearly distinguishes it from related sibling tools like get_resolved_predictions by emphasizing the 'active/pending' scope.

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?

Provides a dedicated 'When to call' section, prerequisites, next steps, and caveats. It names get_prediction_accuracy as a next step, giving useful context. However, it does not explicitly state when not to use the tool or directly name an alternative like get_resolved_predictions, so it falls short of a 5.

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