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Agent Data Tools: Prices and DeFi

Base gas-cost estimates under priority-fee scenarios

mev_simulator

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 $0.04/call via x402 USDC or a card key (/credits), first 25 free; failed calls free. Reads or computes only; not marked read-only because each call is charged.

Input Schema

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

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Goes well beyond the annotations: discloses cost ($0.04/call via x402 USDC or card key, first 25 free, failed calls free), the HTTP 400-without-charge behavior for invalid values, that gas units are fixed typical assumptions rather than per-transaction estimates, and explicitly reconciles readOnlyHint=false ('not marked read-only because each call is charged'). This is exactly the kind of context structured fields cannot convey.

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 scope caveat, then exclusions, then cost. It is dense and slightly list-like, but every clause (assumptions, valid values, 400 behavior, pricing, annotation rationale) earns its place. Minor tightening possible.

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?

With no output schema, the description should ideally hint at the return shape; it says only that it 'estimates' gas costs. However it fully covers pricing, failure modes, input validity, and scope exclusions, so an agent has what it needs to decide to call it, just not to anticipate the response format.

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 enum is self-documenting, so the baseline is 3; the description adds real meaning by explaining what each preset does ('high-mev (3x priority fee)', 'low-gas (half)'), which the schema does not. It does not state the resolved priority-fee formula or units, keeping it from a 5.

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 and resource ('Estimates Base gas costs from current fees and priority-fee presets') and immediately clarifies the scope limiter: it is not a transaction simulator nor an MEV/sandwich-risk tool, which is important given the misleading name 'mev_simulator'. An agent can distinguish it from all siblings (price/audit/report tools) without opening the schema.

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

Usage Guidelines4/5

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

Gives an explicit use case ('Use to budget gas for a Base transaction') plus a concrete example (scenario=standard), and states the negative boundary (no transaction simulation or mempool observation). It does not name an alternative tool to route to instead, but no sibling overlaps meaningfully, so context is clear.

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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