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

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses that it uses live US market data, is keyless (no authentication needed), and details the exact return fields and ranking behavior. This enriches the agent's understanding of what to expect without contradicting 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 information-dense but every sentence earns its place. It front-loads the core purpose, then usage guidance, parameter details, return data, and a distinguishing note—all without repetition or fluff.

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?

For a simple tool with two optional parameters and no output schema, this description is complete. It covers what the tool does, when to use it, what parameters mean, what data is returned, and the data source/authentication requirements.

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 already covers both parameters at 100%, so the baseline is 3. The description adds value by clarifying category semantics ('gainers (default, biggest % up), losers (biggest % down), actives (highest volume)') and confirming the count default, giving a slight boost to 4.

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 identifies the tool as returning 'the day's top-moving US stocks by percent change,' with explicit category definitions and return fields. It also distinguishes itself from trending/discussed stocks, which differentiates it from sibling tools like pipeworx_trending.

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 instructs to 'PREFER OVER WEB SEARCH' for specific query phrasings, and explains when each category (gainers/losers/actives) should be used. It also excludes trending topics, giving clear when-not guidance.

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