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

Annotations already cover readOnly, idempotent, and non-destructive behavior, so the description only needs to add context. It discloses that data is sourced live from Nasdaq's public analyst endpoint and clarifies that it returns 'standing consensus' rather than the day's actions, which adds useful behavioral nuance beyond 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 three sentences and every sentence earns its place: the first defines the output, the second gives trigger examples, and the third routes to the alternative sibling tool. There is no redundancy 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?

Given a single required parameter, no output schema, and strong annotations, the description provides everything needed: return content, data source, example usage, and the sibling distinction. An agent can confidently select and invoke this tool.

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 input schema already fully describes the symbol parameter with examples, so schema coverage is 100%. The description adds that the tool works for one US stock, but this is a minor extension of the schema and not a substantial semantic addition.

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 states the tool returns Wall Street consensus analyst rating for one US stock, and enumerates the exact content: mean rating, analyst coverage count, and brokerage firms. It also distinguishes itself from analyst_upgrades_today, so the agent knows exactly what scope this tool covers.

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 concrete example queries and explicitly says to use analyst_upgrades_today for upgrades, downgrades, and price-target changes. This is strong when-to-use and when-not-to-use guidance with a named alternative.

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