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

Annotations already declare readOnlyHint=true, covering the safety profile. The description adds useful behavioral context beyond that: each row is 'sourced and dated', consensus targets are distinguished from per-firm targets, and firm target rows include 'the news receipt'. This gives the agent expectations about data provenance and granularity.

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 appropriately sized for a multi-mode tool: a one-line purpose statement, a clear intro to the `kind` parameter, and a bulleted list where each bullet earns its place by describing a distinct view. There is no fluff or redundancy, and the important 'sourced and dated' note is placed at the end.

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?

An output schema is present, so the description rightly focuses on distinguishing the five modes rather than return fields. It covers the core behavioral differences (consensus vs per-firm, contents of actions, estimates) and data provenance. Minor gaps like sorting/pagination behavior are not addressed, but the output schema and defaults reduce the need for those details.

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 `kind` parameter is thoroughly documented with 20 aliases and per-value return semantics, which is essential given the schema's 0% description coverage. However, `entity` and `limit` are not described in the text; `entity` is only faintly implied by 'a stock' and `limit` is left to default conventions, so the description does not fully compensate for the schema's lack of detail on those parameters.

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 purpose ('What Wall Street currently thinks about a stock') and breaks out five distinct sub-views, each with concrete content summaries. This clearly distinguishes it from sibling tools like get_earnings by focusing on analyst sentiment rather than raw financials.

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 states that `kind` selects the view and gives a substantive definition for each kind (e.g., ratings = standing analyst ratings, actions = recent upgrades/downgrades). This provides enough context for an agent to choose the right mode, though it does not explicitly contrast with sibling tools or state when not to use this tool.

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