Get Q-Score

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

The description reveals key behaviors beyond annotations: null/empty score handling before ~10am ET, unavailable dimensions contributing 0, and the sector-residualized methodology. These are meaningful operational details that annotations do not convey.

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 dense but well-organized, front-loading the core definition and then detailing the return structure. The listing of components is necessary because there is no output schema, but it is concise enough that every sentence delivers value.

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 complexity, the lack of an output schema, and only two input parameters, the description fully specifies the return fields, caveats, and selection of the scoring horizon. It leaves no critical gap for an agent to select or invoke the tool correctly.

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 description only says 'period selects the scoring horizon', which repeats the schema's description. It does not explain the difference between 30d and 90d or how the choice affects the score. The ticker parameter is self-evident. With 50% schema coverage, the description adds little value here.

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 the tool computes StoQuant's 0-100 composite Q-Score for a ticker, blending multiple dimensions. It explicitly positions it as 'the best single tool for is this a good stock right now', distinguishing it from sibling quote/ML tools.

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 strong usage context ('best single tool for...') and a timing caveat about early morning data not yet refreshed. It stops short of explicitly naming alternatives or when-not-to-use, but the guidance is clear and sufficient.

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