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

Annotations already establish readOnlyHint and non-destructive behavior. The description adds meaningful context beyond annotations: the fixed date window, the 'archive sample' nature, coverage limitations, and the explicit caveat that this is not revenue or earnings. This helps the agent understand the data's scope and limitations 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 tight sentences with no filler. It front-loads the core action and resource, then adds two short clarifications (contents and exclusions). Every phrase earns its place.

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, read-only tool with no output schema, the description is largely complete: it states the resource, data contents, limitations, and exclusions. It could go slightly further by describing the exact return format, but 'including daily data and coverage limitations' gives enough shape for an agent to invoke it correctly.

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 schema coverage is 100%, so the baseline is 4. The description adds useful semantic context about the data content, currency, date range, and limitations, which is more than necessary for a parameterless tool.

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 names a specific action ('Read') and a precise resource: Floatout's fixed September 10–23, 2026 archive sample of gross Hyperliquid builder fees in USDC. It also clarifies what is included and explicitly differentiates this data from Floatout revenue or expected earnings, making the tool's purpose unambiguous.

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 clear context about what data this tool provides and warns that it is 'Not Floatout revenue or expected customer earnings,' which prevents misuse. It does not explicitly compare against sibling tools like list_floatout_plans or read_floatout_page, but the fixed fee-study scope makes the intended use reasonably clear.

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