datahub_subscribe

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

The description discloses key behaviors: recurring subscription, on-chain payment, no per-download fee, renewal extends from current expiry, and spending caps. Without annotations, the description carries the full burden and provides a clear behavioral picture.

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 three sentences, about 50 words, and front-loads the core purpose. Every sentence adds value without redundancy.

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 simplicity and lack of output schema, the description covers the essential aspects: subscription nature, payment, usage, renewal, and spending caps. Missing details about return value are minor.

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 single parameter 'book_id' is well-described in the schema, specifying it must be a dataset with a subscription plan. The description does not add additional parameter details beyond the schema, but schema coverage is 100%, so baseline is appropriate.

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 tool subscribes to a recurring DataHub dataset with time-based access and on-chain payment. It distinguishes from siblings like datahub_buy (for datasets without a subscription plan) and datahub_download (for fetching updates after subscription).

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 indicates when to use the tool: for datasets with a subscription plan, identified via datahub_search. It contrasts with datahub_buy for datasets without a plan, and mentions using datahub_download for fetching updates while subscribed. However, it does not explicitly state when not to use it.

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