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

The annotations already establish readOnly, idempotent, and non-destructive behavior. The description adds meaningful context beyond that: data comes from corporate earnings reports and has been cross-validated by Fodda's analysis pipeline. This explains the provenance and validation behavior without contradicting the 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 two tightly written sentences with no filler. The primary purpose is front-loaded, and the second sentence adds meaningful context about the source content and signal connection.

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 this is a read-only, idempotent, simple list-like tool with 100% parameter schema coverage, the description is sufficient for an agent to invoke it correctly. It clearly describes the result type and source, though it does not provide details about result structure or sorting, which is a minor gap.

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 all five parameters already have clear inline documentation. The description adds no additional parameter-level semantics, such as search behavior or sector filtering, so the baseline 3 is appropriate.

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 states a specific verb and resource: it returns consumer trends derived from corporate earnings reports and cross-validated by Fodda's analysis pipeline. It also clarifies the connection between earnings commentary and trend signals, which helps distinguish this tool from the other earnings-focused siblings.

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 implies when to use this tool: when an agent needs market-validated consumer trends tied to earnings commentary. However, it does not explicitly state when not to use it or name alternative tools such as get_earnings_intelligence or get_earnings_divergence, so the guidance is implied rather than explicit.

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