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

With no annotations, the description carries the full transparency burden. It discloses the rate limit (30 requests/min), the free/no-payment status, and that the response lists what the sample withholds. This is sufficient transparency for a simple read-only, parameterless endpoint.

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?

Three short sentences deliver the key facts: free sample, rate limit, what the paid version adds, and what the response reveals. There is no filler or redundant restating of the tool name.

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 parameterless sample endpoint, the description covers the essential operational details: rate limiting, payment status, missing components, and the alternative tool. Since there is no output schema, a more exact return shape would help, but the description already notes that the response lists what is withheld.

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?

There are zero parameters and the schema is empty, so parameter semantics are not applicable. The baseline of 4 is correct because there is nothing for the description to compensate for.

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 resource as 'the Fear & Greed component of market sentiment' and distinguishes it from the paid get_sentiment by naming what is withheld. The verb 'try' plus 'FREE SAMPLE' makes the action and scope immediately understandable.

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?

It explicitly names the direct alternative get_sentiment and states the difference: this is a free sample, while get_sentiment adds the composite reading and funding-derived component. It doesn't contrast with every sibling, but it gives clear context for the closest comparison.

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