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Gas Prediction

gas.predict
Read-onlyIdempotent

Predict near-future gas prices using moving average and trend analysis of recent block base fees. Returns prediction, trend, and recommendation. Use for a short-horizon fee forecast when planning a transaction. It is not a live quote or a transaction executor; use gas.tracker for current fees and gas.optimize for timing advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNoEVM chain only. Supported chains: base, ethereum, arbitrum, optimism, polygon, bsc, avalanche, zksync, linea, scroll, blast, mantle, gnosis, polygon-zkevm, mode, sei, celo, manta, taiko, fantom, cronos, opbnb, zora, worldchain, metis, fraxtal, kava, zetachain, filecoin, core-dao, aurora, moonbeam, klaytn, bob, canto, monad, tempo, megaeth, arc, plasma, katana, robinhood, pharos, hyperevm.base

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainYesBlockchain queried
errorNo
statsNo
trendNo
currentNo
forecastNo
timestampYesUnix timestamp ms
dataSourceNo
methodologyNo
recommendationNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, open-world, non-destructive, so the safety profile is covered. The description adds methodology (moving-average and trend analysis of block base fees) and states the returned fields (prediction, trend, recommendation) plus explicit scope limits (not a live quote/executor). It stops short of disclosing refresh cadence or latency, which keeps it short of a 5.

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?

Three sentences, front-loaded with the core action, then the return values, then the usage and exclusion guidance. Every sentence carries distinct information with no redundancy.

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

Completeness5/5

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

With an output schema covering return values and annotations covering the safety profile, the description supplies exactly the remaining context an agent needs: what it computes, its horizon, and when to prefer siblings. Nothing required for correct invocation is missing.

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?

There is a single 'chain' parameter with 100% schema description coverage, including the full enum and default. The description adds no syntax or format detail beyond what the schema already provides, so baseline 3 is appropriate.

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?

States a specific verb (predict) and resource (near-future gas prices), names the methodology, and explicitly distinguishes itself from gas.tracker and gas.optimize. An agent can differentiate it from siblings without opening any schema.

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

Usage Guidelines5/5

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

Provides explicit when (short-horizon fee forecast when planning a transaction) and when-not (not a live quote, not a transaction executor), and routes to the correct alternatives (gas.tracker for current fees, gas.optimize for timing advice). Nothing is left to inference.

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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