stock_screener

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

Annotations already convey a safe read operation (readOnlyHint=true, destructiveHint=false). The description adds substantial behavioral detail: limit is capped at 2000 with a single upstream request, sort_by applies server-side over the entire market, exclude_otc affects venue interpretation for 'america,' compact mode reduces payload, and returns include total_matches and local-currency pricing with daily bar semantics. This goes well beyond structured annotation info.

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-organized into Args and Returns sections, with each parameter explained in a single dense line. The purpose sentence is front-loaded, and every sentence adds meaningful detail without filler. Minor redundancy (market-cap ranking mentioned twice) doesn't distract.

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?

With no output schema, the description fully specifies the return envelope (total_matches, returned, rows), row fields, and price/currency semantics, including daily bar definitions. It also covers constraints like the 2000-row upstream limit and OTC exclusion behavior, making the tool's behavior predictable. Despite the lack of error/rate-limit info, the core context is 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 schema provides zero descriptions for all six parameters, so the description carries full burden. It explains each parameter with examples (country list), options (stock_type, sort_by), defaults, and behavioral effects (exclude_otc, compact). This fully compensates for the schema's lack of detail.

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 opens with a specific verb and resource: 'Screen stocks by share type,' positioning it as the API twin of TradingView's common/preferred stock filter. It clearly distinguishes this global screener from sibling tools like egx_stock_screener or top_gainers by emphasizing share-type filtering across multiple markets and market-cap ranking.

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 gives clear context for when to invoke this tool—when common/preferred stock screening across countries is needed, especially with sort_by whole-market semantics like dividend yield or price. It does not explicitly name alternative tools or exclusionary conditions, but the purpose and parameter details make the intended use obvious.

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