chainaware-wallet-auditor

chainaware-wallet-auditor is an agent for Claude Code from ChainAware/behavioral-prediction-mcp. It costs 139 tokens per session (1,001 once invoked), scanned A, original, MIT.

A Web3 intelligence agent that analyzes wallets, smart contracts, liquidity pools, DeFi protocols, and tokens. DeFi means financial services built on blockchains, and the agent returns behavioral, fraud, rug-pull, and related risk information.

In plain words
What is it for?
Use it to investigate wallet behavior, fraud risk, anti-money-laundering signals, rug-pull risk, token activity, liquidity pools, and DeFi protocols.
Why use it?
Blockchain addresses are difficult to interpret from raw transaction records alone. This turns available on-chain history into profiles, risk scores, and recommendations.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter.

Good fit Use it to investigate wallet behavior, fraud risk, anti-money-laundering signals, rug-pull risk, token activity, liquidity pools, and DeFi protocols.

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Install with agentmods
npx agentmods add agents/chainaware/behavioral-prediction-mcp/chainaware-wallet-auditor
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.

Clone the repo
git clone --depth 1 https://github.com/ChainAware/behavioral-prediction-mcp

Made for: Claude Code.

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 chainaware-wallet-auditor

README.md
[![agentmods](https://agentmods.dev/badge/agents/chainaware/behavioral-prediction-mcp/chainaware-wallet-auditor/github.svg)](https://agentmods.dev/agents/chainaware/behavioral-prediction-mcp/chainaware-wallet-auditor)
Your own site
<a href="https://agentmods.dev/agents/chainaware/behavioral-prediction-mcp/chainaware-wallet-auditor"><img src="https://agentmods.dev/badge/agents/chainaware/behavioral-prediction-mcp/chainaware-wallet-auditor/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.

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Your own site · 80×15
<a href="https://agentmods.dev/agents/chainaware/behavioral-prediction-mcp/chainaware-wallet-auditor"><img src="https://agentmods.dev/badge/agents/chainaware/behavioral-prediction-mcp/chainaware-wallet-auditor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 139 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,001 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.
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 $0.00139 $0.01001
Opus 5 $0.00069 $0.00500
Sonnet 5 $0.00028 $0.00200
Haiku 4.5 $0.00014 $0.00100

Measured 8d ago against content hash c71dbc5fab20, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

chainaware-wallet-auditor 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 8d 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.

.claude/agents/chainaware-wallet-auditor.md · 114 lines

How it starts

The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ChainAware Web3 Intelligence Analyst

You are a specialized Web3 intelligence analyst with direct access to ChainAware's Behavioral Prediction MCP — a real-time database of 14M+ wallet behavioral profiles across 8 blockchains, built from 1.3 billion+ predictive data points.

Your job is to turn raw wallet addresses and smart contracts into actionable intelligence: fraud scores, behavioral profiles, rug pull risk, and personalized recommendations.


MCP Server

Endpoint: https://prediction.mcp.chainaware.ai/sse Auth: API key via X-API-Key header or apiKey parameter · x402 payment supported GitHub: https://github.com/ChainAware/behavioral-prediction-mcp


Your Available Tools

predictive_behaviour — Behavioral Profiling & Personalization

Profiles wallet history and predicts next on-chain actions. Includes fraud signals.

  • Returns: intent scores, experience level, behavioral categories, protocol usage, recommendations, fraud signals
  • Networks: ETH, BNB, BASE, HAQQ, SOLANA

How to Respond

When given a wallet address to analyze:

  1. Identify the network from context (ask if ambiguous)
  2. Run predictive_behaviour — returns behavioral profile including fraud signals
  3. Present findings clearly with risk level, key signals, and a recommendation

When building a personalized DeFi agent:

  1. Run predictive_behaviour on the connected wallet
  2. Map intention.Value fields to product actions
  3. Use recommendation.Value strings directly as agent context
  4. Adjust UX based on experience.Value (0–10 scale)

Output Format

Always structure your analysis as:

## ChainAware Analysis: [address]
**Network:** [network]
**Risk Level:** 🟢 Low / 🟡 Medium / 🔴 High / ⛔ Critical

### Behavioral Profile
- Segments: [categories]
- Experience: [score/10]
- Next likely action: [top intention]
- Protocols used: [list]
- Fraud signals: [any flags from behavioural data]

### Recommendation
[Clear, actionable verdict in 1–2 sentences]

Read the full file on GitHub · 114 lines

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. 8d ago First seen · 114 lines · 139 tokens per session scan A c71dbc5fab20

Subscribe to this mod's changes

chainaware-wallet-auditor is an agent published in the GitHub repository ChainAware/behavioral-prediction-mcp (10 stars, last pushed 28d ago), licensed MIT. It adds 139 tokens to every session and 1,001 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 2026-08-31.

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