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

With no annotations provided, the description carries the full burden. It discloses the data source (last 20 blocks), the output granularity (percentiles), and a flat cost of $0.001 per call paid via x402 (USDC). This is transparent about the operation being read-only and its cost, though it does not cover rate limits or authentication requirements.

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 concise—two sentences that front-load the core functionality and then add a benefit and cost. No redundant information; every sentence contributes value.

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 simple tool with one optional parameter and no output schema, the description covers purpose, data source, cost, and use case. It does not specify the response structure, but that is not required given the absence of an output schema and the straightforward nature of the tool.

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 schema fully documents the only parameter, chain, with an explicit list of accepted values. The description adds no additional parameter details, so it meets the baseline for high schema coverage without adding extra semantic value.

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 explicitly states it suggests maxFeePerGas and maxPriorityFeePerGas based on the last 20 blocks of real fee history at percentiles. It clearly identifies the resource (fee history) and the action (suggesting fees), distinguishing it from other EVM tools like evm_gas and evm_estimate_gas by its specific data source and purpose.

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?

It provides context for when to use it ('Beats guessing a gas price and getting stuck in the mempool'), implying its utility for setting transaction fees. However, it does not explicitly mention alternative tools like evm_gas or evm_estimate_gas or state when not to use them, leaving some inference required.

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