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

Annotations are all false and offer no safety/side-effect hints, so the description carries the burden. It adds useful behavioral context: per-query billing, 0.01 USDC cost, max 20 queries/session, and a paid-vs-free distinction. However, it does not disclose what happens on unfunded sessions, how results are returned, or how delivery_receipt/sandbox_receipt affect execution.

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 information-dense sentences with no fluff. The core action is front-loaded, then the free alternative, specific listing details, and the required sequence follow in order. Every clause earns its place.

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?

Without an output schema and with mostly unhelpful annotations, the description must provide enough context for correct invocation. It gives pricing and workflow but omits parameter meanings, expected response shape, and failure/edge-case behavior. An agent would struggle to fill k, query, and delivery_receipt correctly.

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 only 40% (session_id and sandbox_receipt have descriptions); query, k, and delivery_receipt are undocumented in both the schema and the description. The description mentions the dataset and pricing but says nothing about how to construct the query, what k controls, or what delivery_receipt is for. It does not compensate for the coverage gap.

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 verb (buy per-query access) and resource (live data listings), names a concrete listing (pubmedwatch at 0.01 USDC), and distinguishes the tool from data_preview and the session lifecycle steps via the explicit sequence. An agent can tell exactly what this tool does relative to siblings.

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?

Explicitly routes free first-use to data_preview ('first taste free via data_preview') and lays out the required predecessor steps: data_session_open → data_session_fund → data_session_query. This gives clear when-to-use and when-not-to-use guidance.

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