agentmods.dev

evm-bytecode-analysis

A local analyzer for deployed EVM runtime bytecode, the machine code running inside an Ethereum-compatible smart contract.

In plain words
What is it for?
Use it to reconstruct an ABI, find function selectors, examine storage access, inspect control flow, or integrate the analyzer into a Rust, Go, Python, or JavaScript application.
Why use it?
It helps inspect contracts when the source code or ABI—the description of available functions and data—is missing or unverified.

Skill for Claude CodeCodex

461 17d ago A scan 135 tokens original MIT
View the source file cdump/evmole
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/cdump/evmole/evm-bytecode-analysis
Any agent
npx skills add cdump/evmole --skill evm-bytecode-analysis
Clone the repo
git clone --depth 1 https://github.com/cdump/evmole

Made for: Claude Code, Codex.

Per session 135 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 846 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00135 $0.00846
Opus 5 $0.00068 $0.00423
Sonnet 5 $0.00027 $0.00169
Haiku 4.5 $0.00014 $0.00085

Measured 2d ago against content hash 0bc7c6eb5437, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

evm-bytecode-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agent/skills/evm-bytecode-analysis/SKILL.md · 72 lines

How it starts

The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.

EVM Bytecode Analysis

Use EVMole for deterministic, local extraction from deployed EVM runtime bytecode.

Route by intent

  • To answer a question from supplied runtime bytecode, use the analysis workflow below. Prefer the MCP tool when available and otherwise use the JSON CLI.
  • To add published EVMole to a separate application's code, use the native library for the project's language instead of invoking the MCP server or agent JSON adapter from product code. Read references/libraries.md for package names, entry points, and documentation.
  • To implement, debug, refactor, or review EVMole itself, follow that repository's contributor instructions and inspect its source. Do not use a published package, MCP server, or JSON CLI as a substitute for understanding the implementation. Read this skill only when the repository task targets the CLI, MCP server, agent adapter, schemas, interpretation behavior, or the skill itself.
  • Use the JSON CLI as an application process boundary only when the user explicitly wants a subprocess or a language without a supported binding.

Workflow

  1. Obtain or confirm deployed runtime bytecode. Treat an address as an address, not bytecode; ask for the runtime code or use another authorized RPC tool to fetch it. Do not ask EVMole to execute or strip creation bytecode.

  2. Select only the features needed:

    • selectors for function selectors and dispatch locations.
    • arguments for inferred argument lists; this implies selectors.
    • stateMutability for inferred mutability; this implies selectors.
    • storage or transientStorage for inferred storage access.
    • metadata for terminal compiler metadata.
    • disassembly, basicBlocks, or controlFlowGraph for instruction and control-flow evidence.

  3. Prefer the analyze_evm_bytecode MCP tool when available. Otherwise run the JSON CLI:

    npx -y evmole@latest analyze --bytecode 0x... --include selectors,arguments,stateMutability,storage

Read the full file on GitHub · 72 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 72 lines · 135 tokens per session scan A 0bc7c6eb5437

Subscribe to this mod's changes

evm-bytecode-analysis is a skill published in the GitHub repository cdump/evmole (461 stars, last pushed 17d ago), licensed MIT. It adds 135 tokens to every session and 846 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Languagesbytecodeethereumevmsolidityweb3
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