financial_reasoning_query

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

No annotations are provided, so the description carries full burden. It states the tool uses StockUp Quan AI and real-time stock quotes, but omits details like rate limits, idempotency, or whether it makes external API calls. This is average transparency for a query tool.

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 a single, front-loaded sentence with examples, conveying the core purpose without unnecessary words. Every part adds 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 no output schema and no annotations, the description leaves out details about response format, error handling, or usage constraints. For a simple query tool, it is minimally adequate but not comprehensive.

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 mentions 'grounded with real-time stock quotes', which hints at the googleSearch parameter's role, but no additional semantic context beyond the schema is provided. Does not significantly enhance understanding.

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 a specific verb ('Send') and resource ('natural language financial prompts to StockUp Quan AI'), and provides clear examples (stock valuations, sentiment audits, etc.). With no sibling tools, differentiation is unnecessary, but it uniquely identifies the tool's purpose.

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 clearly indicates the tool is for financial prompts and is grounded with real-time stock quotes, implying use for finance-related queries. However, no explicit 'when to use vs alternatives' guidance is provided, though the lack of sibling tools reduces the need.

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