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

With no annotations, the description carries the full behavioral burden and does disclose useful non-schema traits: row-count pricing, a minimum charge, a stated max range, free MCP access, and a paid production endpoint. It still omits rate limits, authentication needs, and explicit read-only/side-effect information.

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 two sentences and front-loads the core capability before moving to pricing and availability. It is dense but not repetitive, and the paid endpoint is relevant context rather than padding.

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 three-parameter export tool with a fully documented schema and no output schema, the description covers the basic purpose, format, and pricing. It remains incomplete on sibling differentiation, explicit date-range constraints, and operational details such as rate limits or auth.

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 100%, so the schema already documents from, to, and format. The description reinforces the date-range and JSON/CSV aspects but adds no syntax, timezone, inclusivity, or range-bound details beyond the schema.

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 resource and scope: raw Ethereum gas price samples over a date range, with JSON or CSV output. It distinguishes the tool from aggregate/metric siblings by emphasizing raw samples and export, though it does not explicitly name a sibling for contrast.

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 notes that the data is free via MCP and that the same data is available pay-per-call for production/agentic use, which gives some usage context. However, it does not explain when to choose this tool over sibling gas tools such as get_gas_metrics or get_gas_comparator.

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