quant_check_events

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

Annotations already mark the tool as readOnly, idempotent, and not destructive. The description adds valuable context: it returns upcoming events with null fields, the default window of 3 days, and the risk handling. No contradictions with annotations.

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 with a clear first sentence, usage guidance, and explicit Args/Returns sections. It is efficient and front-loaded, though slightly longer than minimal.

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 purpose and existing annotations/output schema, the description covers purpose, usage, and behavioral nuances. It explains how to use the output with another tool and what to do when data is missing, making it fairly 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?

The input schema already provides descriptions for ticker and response_format. The description lists the same parameters in Args and adds return field names. While schema coverage is indicated as 0%, the schema actually has good descriptions, so the description adds marginal value.

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 clearly states it provides 'Upcoming earnings and dividend events for a ticker,' specifying the action and resource. It distinguishes this tool from siblings like quant_score_decision by mentioning how to pass days_to_earnings to that tool.

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 explicitly tells when to use this tool (to check earnings/dividends before entries) and what to do with the output: pass days_to_earnings to quant_score_decision. It also advises checking the IR page when data is null, giving clear alternatives.

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