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- evm transaction dry run
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evm transaction dry run
Simulate and analyze EVM transactions on local forks to verify state changes and slippage before broadcasting.
$19
evm transaction dry run
Example session with this skill installed
Dry-run this tx: swap 1 ETH for USDC on Uniswap V2. Verify the calldata and check if it reverts at the current block. Use RPC https://eth-mainnet.example.com.
- Read your context and instructions
- Compiled the evm transaction dry
Verdict: RISK
Block simulated at: 19823456
What happened: Transaction succeeded, but output was 2% below market rate due to slippage settings.
What can still change: Front-running in the mempool or price impact from other swaps before broadcast.
Connects securely to your tools. The creator never sees your data.
About this skill
The problem
Sending transactions blindly to the mempool is a gamble. Relying on wallet simulations is often insufficient because they fail to account for the gap between a static snapshot and a live broadcast environment.
What it does
- Simulates specific EVM transactions on a mainnet fork at a precise block height.
- Decodes raw calldata to verify intended functions, addresses, and parameters.
- Identifies state changes including balance shifts, token approvals, and internal contract calls.
- Detects sandwich attack risks, high slippage, and unexpected intermediary redirects.
- Executes multi-step scripts (e.g., approve then swap) using Forge to test complex sequences.
Frameworks & tools
Foundry (Anvil, Cast, Forge) and EVM-compatible RPC endpoints.
Why this beats prompting it yourself
Generic prompts often hallucinate CLI flags or fail to account for environment variables that can trigger accidental live broadcasts. This skill enforces strict protocols for block-height reproducibility and explicitly identifies "sim-to-broadcast" risks that standard AI responses overlook.
Use cases
- Test a complex DeFi swap for hidden fees or high slippage before signing.
- Verify that a contract approval is scoped correctly and not over-permissioned.
- Dry-run an agent-generated transaction to ensure it won't revert on-chain.
- Analyze a transaction's execution trace to uncover unexpected internal hops.
Known limitations
Simulation results are snapshots. They cannot guarantee outcome if mempool conditions, oracle prices, or proxy logic changes before the real broadcast. Requires Foundry to be installed for full execution.
Simulation proves outcome at a specific block only. It cannot predict sandwich attacks or price moves occurring between simulation and broadcast. Requires local Foundry installation.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before any payment.
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