datahub_buy

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It covers the purchase flow, settlement (x402 on Solana), token options, and that spending caps apply. However, it omits details about error conditions, refunds, or post-purchase state changes, which would improve transparency.

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 sentences long, front-loading the core action and result. Every phrase adds value: the settlement info, default token, alternative, and the caveat about re-buying. No redundant words.

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 has 2 parameters, no output schema, and no annotations, the description covers the essential context: what the tool does, what information is needed (book_id, token), and key gotchas (spending caps, duplicate purchase). However, it could be more complete by describing error handling or the download link format.

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%, but the description adds value beyond the schema: for token, it explains the default and wallet requirements; for book_id, it specifies the correct format (uuid from datahub_search) and warns against duplicate purchases. This enriches the schema definitions.

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 the action (buy), resource (DataHub dataset), and the outcome (returns download link). It also distinguishes from siblings like datahub_download (for re-fetching) and datahub_subscribe by mentioning the one-time purchase nature.

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 specifies when to use this tool (to buy a dataset) and when not to (buying again if already owned, use datahub_download instead). It also notes the default token (USDC) and alternative (USDT), and mentions spending caps, providing clear usage guidance.

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