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

Annotations already cover read-only, idempotent, open-world, and non-destructive behavior. The description adds valuable context beyond annotations: it is free, requires no wallet or payment, and takes no arguments. No contradictions with 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?

Two tightly written sentences, front-loaded with [FREE] and the core purpose. Every phrase adds useful selection information: sample nature, target sibling, cost model, and lack of required arguments. No waste.

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 zero-parameter preview with no output schema, the description is adequate: it identifies the source tool, clarifies the sample nature, and notes no payment or arguments are needed. It could mention whether the sample is static or truncated, but nothing critical for correct invocation is missing.

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 tool has zero parameters and 100% schema coverage, so parameter semantics are inherently minimal. The description reinforces this by stating 'no arguments needed', which matches the empty schema. Baseline for zero-param tools is 4.

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?

States the tool returns a sample response for edgar_bundle and explicitly frames it as a free preview before paying. It clearly distinguishes itself from the paid sibling edgar_bundle, but relies on the title or external knowledge of edgar_bundle to know what data is actually sampled.

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?

Names the condition and alternative: use this to see the shape before paying 0.03 USDC for edgar_bundle. It also clarifies no wallet, payment, or arguments are needed. No explicit when-not guidance, but 'sample' implicitly limits use to preview rather than production data.

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