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

Annotations already declare readOnlyHint=true and idempotentHint=true, but the description adds valuable behavioral insights: the per-call cost range ($0.25–$0.60) and the existence of free alternatives. These go beyond the structured annotations, though the description doesn't detail return formats or error behaviors, which is acceptable given the strong annotation coverage.

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 two concise sentences: the first lists all capabilities, the second provides cost and alternative guidance. It is front-loaded, zero-waste, and every piece of information earns its place.

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 (five optional parameters, six modes, no output schema) and strong annotations, the description sufficiently covers purpose, cost, and alternatives. It does not describe return shapes, but that is acceptable since the schema and sibling tool context already provide adequate guidance for a user to 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?

Schema description coverage is 100%, with each parameter well-documented in the schema itself. The description adds no new parameter-level semantics beyond relabeling alpha_ranked as 'alpha-ranked gainers with quality filters' and clarifying regime, but the schema already covers these meanings. Baseline 3 is appropriate because the schema does the heavy lifting.

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 a scanner for live market data and enumerates six distinct scan types (top gainers, movers, alpha-ranked gainers, altseason, technicals, regime). This specificity distinguishes it from sibling tools like get_top_movers by covering multiple use cases in one call.

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 tells users this is a paid tool and points them to list_einstein_capabilities for free alternatives, offering context on when to avoid this tool. It does not explicitly name which alternatives correspond to which scan types, leaving a slight gap in direct comparisons, but still provides clear cost-related guidance.

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