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

The description adds meaningful behavioral context beyond the annotations by disclosing that attribution is Etherscan-derived, strong on Ethereum, and sparse on other chains. This informs the agent about data quality variations, which annotations do not cover.

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 sentences with no waste: the first lists the key coverage dimensions, the second adds a critical caveat. The core concept is front-loaded, and the caveat is placed logically after the list.

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?

For a zero-parameter read-only tool without an output schema, the description adequately summarizes the returned data types and the data-quality limitation. It could be more explicit about the exact response format, but it covers the essential information an agent needs to understand what the tool provides.

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?

There are zero parameters, so schema coverage is trivially 100%. The description does not need to explain parameters, and the baseline for zero-parameter tools is 4. No additional parameter semantics are required.

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?

Clearly states it provides per-chain coverage metrics, listing specific data points: tokens mapped, labelled addresses, whale transactions, and attribution counts. The verb is implied but the resource and scope are explicit. It does not explicitly differentiate from sibling coverage tools like get_data_coverage, but the focus on chains is evident.

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?

Implied usage for obtaining chain-level coverage data, but there is no explicit guidance on when to use this over alternative coverage tools. The caveat about Etherscan-derived attribution provides context but not selection criteria or exclusions.

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