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Gas Oracle

gas_oracle
Read-onlyIdempotent

[$0.005 USD per call] Live gas prices (gwei) for Ethereum, Base, Polygon. Live-RPC sourced, no key required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paymentNoOptional x402 payment proof (EIP-3009 signed authorization). Call once without it to receive the payment requirements, then retry with the proof.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {}
      +]
  2. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, covering safety. The description adds valuable behavioral context: a per-call cost of $0.005, that it is live-RPC sourced, and that no API key is required. This goes beyond the annotations and helps the agent understand the operational nature, though it does not detail rate limits or exact response format.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that packs the cost, purpose, chains, source, and key requirement into a compact format. Every element earns its place, and the most critical operational detail (cost) is placed first. There is no fluff or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple and the description covers the core information: what it returns (gas prices in gwei), for which chains, and the source. It does not explicitly state the output structure (e.g., a JSON object with per-chain prices), but given the simplicity and the fact that no output schema is provided, the description is sufficient for an agent to understand how to call and interpret the result. The payment flow is described in the schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has one optional parameter 'payment' with a comprehensive description explaining the x402 proof and the retry pattern. Schema description coverage is 100%, so the description does not need to add parameter details. The main description mentions cost but does not clarify that payment proof is needed; that is left to the schema. Thus the description adds no extra semantic value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool provides live gas prices in gwei for three specific chains (Ethereum, Base, Polygon). It names the resource and source (Live-RPC) and notes no key required, which distinguishes it from potential siblings that might offer similar market data. The purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly mention when to use this tool versus alternatives, nor does it list exclusions. However, the highly specific purpose (gas prices) makes it obvious for an agent when to invoke it. There is no guidance on when not to use it or what other tools might be better for related needs, so it relies on implication.

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

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