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Base gas-cost estimates under priority-fee scenarios: estimate Base transaction gas costs under different priority-fee scenarios

mev_simulator
Read-only

Estimates Base gas costs from current fees and priority-fee presets. Fixed gas units (100k simple, 250k complex, 180k liquidity) are typical assumptions, not transaction-specific estimates or quotes. Valid values: standard, high-mev (3x priority fee), low-gas (half); invalid values return HTTP 400 without charge. No transaction simulation, mempool observation, or MEV/sandwich-risk measurement. Use to budget gas for a Base transaction. Example: scenario=standard. Price $0.01/call via x402 USDC or a card key (/credits), first 25 free; failed calls free. Reads or computes only and changes nothing; each call is charged, so repeats are not free.

Input Schema

NameRequiredDescriptionDefault
scenarioNoOne of standard, high-mev, low-gas (default: standard)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

Goes well beyond the readOnly/destructive annotations by disclosing pricing ($0.01/call, first 25 free, failed calls free), that invalid enum values return HTTP 400 with no charge, and that repeat calls are billed - consistent with idempotentHint=false. It also flags that the gas-unit figures are assumptions rather than quotes, which is exactly the caveat an agent needs to avoid overclaiming precision.

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

Conciseness4/5

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

Front-loaded with the core purpose and caveats, and every sentence carries operational information. It is somewhat dense and packs pricing, validation, and exclusions into long clauses, but nothing is filler.

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?

Covers cost, failure modes, assumptions, and exclusions thoroughly for a one-parameter tool. The one remaining gap is that with no output schema, the description never says what the response actually contains (field names, units, whether cost is in wei/ETH/USD), leaving the agent to infer the return shape.

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

Parameters4/5

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

Schema coverage is 100% and the single enum is documented, so the baseline is 3. The description earns extra credit by explaining what the presets mean (high-mev = 3x priority fee, low-gas = half) and the default, plus the failure behavior for invalid values, which the schema alone does not convey.

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 opening sentence gives a specific verb and resource - estimating Base gas costs under priority-fee scenarios - and the fixed gas-unit figures make the output shape concrete. No sibling tool covers gas or fee estimation, and the description explicitly disclaims transaction simulation and MEV measurement, so an agent can place it unambiguously.

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?

States the intended use ('Use to budget gas for a Base transaction'), gives the valid preset values with their meanings, and explicitly rules out what it does not do (no simulation, no mempool observation, no sandwich-risk measurement). This is when-to-use plus when-not-to-use, which is the top of the scale.

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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