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

With no annotations provided, the description carries the full burden, and it discloses important behavior: it is a paid tool, credits cost $1.00-$1.49, uncredentialed calls return a 402 payment envelope, and X-API-KEY must be set. This is useful operational context beyond what the schema provides.

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 one dense sentence and front-loads the purpose before the payment details. It is efficient and avoids filler, though it packs several billing, endpoint, and header details into a long clause that could be more readable with clearer sentence separation.

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?

Considering the tool has one simple parameter, no output schema, and no annotations, the description is largely complete for selection and invocation: it covers purpose, payment, token/auth, failure behavior, and scope. Some example questions or expected output hints would make it stronger, but they are not necessary for such a flexible NL 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 schema has only one parameter, 'question', and the schema description already says it accepts natural-language questions about markets. The tool description reinforces this and adds payment context, but it does not add format examples, constraints, or additional semantic detail beyond the high schema coverage.

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 identifies the tool as a natural-language market analysis endpoint covering any instrument, sport, race, or prediction market. This is reasonably clear and distinguishes it from the structured scan/signal/quote siblings, though the tool name 'analysis' is generic and there is no explicit verb like 'answer' or 'return'.

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 usage: ask any natural-language question about markets. It does not explicitly say when to prefer this instead of sibling scan/signal/quote tools, nor does it list exclusions. The 'any question' framing gives context, but a clearer comparison to specialized siblings would improve it.

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