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

Beyond the annotations, the description discloses that each query costs 0.01 USDC and is capped at 20 queries per session, which are critical behavioral constraints. It also signals the paid nature and points to a free preview via data_preview. It does not explicitly describe balance deduction or DeliveryReceipt signing, but the cost and quota information is meaningful context.

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?

Three sentences, compact and front-loaded with the core purpose before giving the listing details and required sequence. The phrase 'AI app demos & live web UIs' adds color rather than invocation-critical information, so it is not a perfect 5, but there is little 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?

The description provides the essential lifecycle, cost, and per-session query cap, which is strong contextual coverage. However, with no output schema and only 40% parameter documentation, an agent still lacks guidance on output format, error behavior, and the role of delivery_receipt/k, so completeness is only partial.

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 description coverage is only 40%, and the tool description does not compensate. It does not explain the semantics of query, k, or delivery_receipt; only session_id and sandbox_receipt have schema-level descriptions. The description mentions per-query pricing but gives no guidance on what a valid query looks like or how k/receipts influence execution.

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 identifies the operation as per-query access to live data listings and anchors it in the data_session_open → data_session_fund → data_session_query sequence, so an agent can tell this runs queries against a funded session. It also distinguishes itself from data_preview by noting the first taste is free there. The 'Buy' phrasing is slightly commercial, but the resource and verb are clear enough.

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 sequence data_session_open → data_session_fund → data_session_query clearly tells the agent when this tool is intended to be used, after opening and funding a session. It also points to data_preview as the free alternative. It does not spell out explicit 'don't use this if...' conditions, but the sequence and 'funded session' implication provide adequate guidance.

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