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

No annotations exist, so the description bears full responsibility. It discloses the tool's nature as an estimate, the constant-product model, aggregation across venues, and the paid pricing structure. More details on caching, error handling, or auth would improve it, but the current description adds significant behavioral context beyond the schema.

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 a single efficient paragraph that front-loads the purpose, includes essential usage and pricing details, and contains no unnecessary words. Every sentence provides value.

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 the tool's complexity (slippage curve estimation) and the absence of an output schema, the description adequately explains the model, parameters, and output concept. It could hint at the output structure (e.g., list of size-impact pairs), but it is largely complete for its purpose.

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?

Schema coverage is 100%, and the description reinforces parameter usage with the shorthand 'Send { ticker, sizeUsd?, feePct? }' and adds context like 'omit for a default ladder ($1k-$250k)'. It clarifies the output is a curve of % impact vs. trade sizes, adding meaning beyond the schema descriptions.

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 it provides a 'pre-trade price-impact / slippage curve' for tokenized stocks, with specificity on estimated % impact, trade sizes, venue aggregation, and the constant-product model. It distinguishes itself from sibling rh_* tools like rh_liquidity_map or rh_pool by focusing on slippage estimation.

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 provides usage instructions ('Size orders before you send them' and 'Estimate only') but lacks explicit guidance on when not to use this tool or mention of alternatives. It implies pre-trade estimation but doesn't address scenarios where more accurate data or execution is needed.

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