Screen US stocks

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

With no annotations, the description carries full burden. It discloses that results are sorted and paginated, and explains filtering mechanics for numeric and categorical parameters. It does not mention auth, rate limits, or edge cases, but for a screening tool this is adequate.

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?

Three concise sentences, front-loaded with purpose, then usage guidance. Every sentence adds value with no redundancy.

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 8 parameters and no output schema, the description covers filtering, sorting, pagination, and references list_filters for metric discovery. It leaves out details on columns and error handling, but overall sufficient for correct 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 coverage is 100%, so baseline is 3. The description adds context about using list_filters for metric names and clarifies that sectors and industries are separate, but does not significantly extend beyond the schema descriptions.

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 screens US stocks by fundamental and technical criteria, listing categories like valuation, growth, and dividends. It distinguishes from siblings such as screen_etfs and get_stock_details by specifying US stocks and referencing list_filters for metric discovery.

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?

It advises using list_filters to discover metric names and explains that numeric filters use min/max while sectors and industries have separate parameters. However, it does not explicitly contrast with screen_etfs or search_stocks, though sibling names provide context.

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