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Automaton Token Safety

simulate_base_transaction

FREE, runs locally against Base Mainnet RPC. Dry-run a transaction before sending it: eth_call + eth_estimateGas at the latest block. Predicts whether it will revert and decodes the reason (Error(string), Panic(uint256) codes, custom-error selector, or node rejection such as insufficient funds). Returns { ok, willRevert, revertReason, estimatedGas, returnData }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesTarget contract or recipient address on Base (0x...).
dataNoCalldata as 0x-hex (default 0x for a plain ETH transfer).
fromNoOptional sender address; needed for balance/allowance-dependent calls.
valueNoETH value in wei, decimal or 0x-hex (default 0).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

With no annotations to lean on, the description carries the full burden and does so well: it discloses the cost (FREE), execution locality (runs locally against Base Mainnet RPC), the exact RPC methods and block height (eth_call + eth_estimateGas at latest block), the non-mutating nature of the dry-run, and the specific revert decoding categories it can detect.

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?

Dense but waste-free: the free/local nature is front-loaded, the mechanism and revert-decoding detail follow, and the return shape closes it out. Every clause conveys actionable information.

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?

There is no output schema, but the description compensates by enumerating the return fields { ok, willRevert, revertReason, estimatedGas, returnData } and the revert-decode taxonomy. Given no annotations, the behavioral and return coverage is strong, though sender/permission prerequisites are left to the schema's from-field description.

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?

Schema description coverage is 100%, so the schema already documents all four parameters, including defaults for data and value. The description adds no additional syntax or format guidance beyond what the schema provides, so the baseline 3 applies.

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

Purpose4/5

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

States a specific verb and resource: dry-run/simulate a transaction on Base, performed via eth_call + eth_estimateGas. However, it never distinguishes itself from the sibling tx_simulate, which appears to be a competing simulation tool, so an agent cannot tell the two apart from the text alone.

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?

"Dry-run a transaction before sending it" gives clear situational context for when to reach for this tool. It stops short of stating when NOT to use it or naming the alternative (tx_simulate) for cases it does not cover.

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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