mev-analysis

mev-analysis is a skill for Claude Code from agiprolabs/claude-trading-skills. It costs 22 tokens per session (3,158 once invoked), scanned A, original, MIT.

An analysis of maximal extractable value, or MEV—the profit that validators and specialised traders can make by changing the order of transactions in a block. It focuses on Solana decentralised-exchange trades, especially sandwich attacks and arbitrage.

In plain words
What is it for?
Use it to assess MEV risk, detect sandwich attacks, estimate possible losses, and choose protections for Solana DEX trading.
Why use it?
It helps explain why a swap may receive a worse price when another trader observes and places transactions around it. It also identifies ways to estimate and reduce this exposure.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the trading-skills plugin — 68 skills shipped together

not rated 354repo +12 8d ago A scan Socket: passSnyk: warnSkillSpector: pass 22 tokens original MIT

Good fit Use it to assess MEV risk, detect sandwich attacks, estimate possible losses, and choose protections for Solana DEX trading.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/agiprolabs/claude-trading-skills/mev-analysis
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.

Any agent
npx skills add agiprolabs/claude-trading-skills --skill mev-analysis
Clone the repo
git clone --depth 1 https://github.com/agiprolabs/claude-trading-skills

Made for: Claude Code.

Or install trading-skills, the plugin that ships this one along with the rest of its 68 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for mev-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/agiprolabs/claude-trading-skills/mev-analysis/github.svg)](https://agentmods.dev/skills/agiprolabs/claude-trading-skills/mev-analysis)
Your own site
<a href="https://agentmods.dev/skills/agiprolabs/claude-trading-skills/mev-analysis"><img src="https://agentmods.dev/badge/skills/agiprolabs/claude-trading-skills/mev-analysis/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for mev-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/agiprolabs/claude-trading-skills/mev-analysis"><img src="https://agentmods.dev/badge/skills/agiprolabs/claude-trading-skills/mev-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,158 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 21 Mar 2026
  • Snyk warn 21 Mar 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00022 $0.03158
Opus 5 $0.00011 $0.01579
Sonnet 5 $0.00004 $0.00632
Haiku 4.5 $0.00002 $0.00316

Measured 12d ago against content hash 48f45e49c39b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

mev-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 12d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/mev_risk_estimator.py, scripts/sandwich_detector.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/mev-analysis/SKILL.md · 321 lines

How it starts

The opening of the file, as written. The whole thing — 321 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MEV Analysis for Solana DEX Trading

Maximal Extractable Value (MEV) is the profit that validators and searchers can extract by reordering, inserting, or censoring transactions within a block. On Solana DEXes, MEV primarily manifests as sandwich attacks against swaps, cross-DEX arbitrage, and liquidation extraction. This skill covers detection, estimation, and protection strategies.

What Is MEV on Solana?

MEV occurs when someone with transaction ordering power profits at other traders' expense. On Solana, the MEV supply chain works as follows:

  1. You submit a swap through an RPC endpoint
  2. Searchers observe your transaction (via RPC forwarding, block engine access, or leader TPU sniffing)
  3. Searcher constructs a profitable bundle (e.g., sandwich your swap)
  4. Bundle submitted to Jito block engine with a tip to the validator
  5. Validator includes the bundle in the block, earning the tip
  6. You receive worse execution; the searcher profits the difference

How Solana MEV Differs from Ethereum

Aspect Ethereum Solana
Block time 12 seconds ~400ms slots
Mempool Public mempool No mempool (but tx visible in transit)
Ordering Proposer-builder separation (PBS) Jito block engine (~85%+ validators)
Bundle system Flashbots bundles Jito bundles with tips
MEV cost Gas priority fees Jito tips (SOL)
Latency pressure Moderate Extreme (sub-100ms decisions)

Key Solana-specific factors:

  • No public mempool: Transactions flow RPC → TPU → Leader, but searchers tap into this flow via Jito's block engine and modified validators
  • Known leader schedule: The leader (block producer) schedule is known ~2 epochs ahead, letting searchers target specific leaders
  • Jito dominance: ~85%+ of validators run the Jito-modified client, making Jito bundles the primary MEV vector
  • Speed: 400ms slots mean MEV bots must operate in microseconds, favoring co-located infrastructure

Read the full file on GitHub · 321 lines

Files

What ships with it

4 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. 12d ago First seen · 321 lines · 22 tokens per session scan A 48f45e49c39b

Subscribe to this mod's changes

mev-analysis is a skill published in the GitHub repository agiprolabs/claude-trading-skills (354 stars, last pushed 8d ago), licensed MIT. It adds 22 tokens to every session and 3,158 once invoked, about $0.0001 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.