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chainaware-behavioral-prediction

Use this skill whenever a user asks about wallet safety, fraud risk, rug pull detection, wallet behavior analysis, DeFi personalization, on-chain reputation…

Skill by ChainAware

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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/chainaware-chainaware-behavioral-prediction

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About

Use this skill whenever a user asks about wallet safety, fraud risk, rug pull detection, wallet behavior analysis, DeFi personalization, on-chain reputation scoring, AML checks, token ranking by holder quality, airdrop screening, lending risk, token launch auditing, or AI agent trust scoring. Triggers on questions like: is this wallet safe?, will this pool rug pull?, what will this address do next?, score this wallet, detect fraud for address, personalize my DeFi agent, rank this token, top AI tokens, best holders of this token, check this contract, is this token safe?, profile this wallet, KYC this address, pre-screen this user, AML check this wallet, is this address suspicious?, screen this wallet before onboarding, what is the risk score of this address?, analyze on-chain behavior, is this LP safe to deposit?, will this contract rug?, what DeFi products suit this wallet?, segment this user, what is this wallet's experience level?, find strong token holders, which token has the best community?,rank tokens by holder quality, should we list this token?, audit this launch, is this deployer trustworthy?, vet this IDO, launch safety check, screen this airdrop list, filter bots from airdrop, rank these wallets for token distribution, fair airdrop allocation, assess this borrower, what collateral ratio for this wallet?, lending risk for 0x..., what interest rate for this borrower?, should I lend to this wallet?, screen this AI agent, is this agent wallet safe?, agent trust score for 0x..., check the feeder wallet for this agent, can I trust this agent?, route this wallet to onboarding, is this user a beginner?, skip onboarding for this wallet?, or any request to analyze a blockchain wallet address, smart contract, token, or AI agent for risk, behavior, intent, community strength, or trustworthiness. Also use when integrating the ChainAware MCP server into Claude Code, Cursor, ChatGPT, or any MCP-compatible AI agent framework.

Use cases: documents, backend, security, agent-building

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
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Secrets
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Install scripts
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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/chainaware-behavioral-prediction

What's inside

Skill name
chainaware-behavioral-prediction
Description
Use this skill whenever a user asks about wallet safety, fraud risk, rug pull detection, wallet behavior analysis, DeFi personalization, on-chain reputation scoring, AML checks, token ranking by holder quality, airdrop screening, lending risk, token launch auditing, or AI agent trust scoring. Triggers on questions like: is this wallet safe?, will this pool rug pull?, what will this address do next?, score this wallet, detect fraud for address, personalize my DeFi agent, rank this token, top AI tokens, best holders of this token, check this contract, is this token safe?, profile this wallet, KYC this address, pre-screen this user, AML check this wallet, is this address suspicious?, screen this wallet before onboarding, what is the risk score of this address?, analyze on-chain behavior, is this LP safe to deposit?, will this contract rug?, what DeFi products suit this wallet?, segment this user, what is this wallet's experience level?, find strong token holders, which token has the best community?,rank tokens by holder quality, should we list this token?, audit this launch, is this deployer trustworthy?, vet this IDO, launch safety check, screen this airdrop list, filter bots from airdrop, rank these wallets for token distribution, fair airdrop allocation, assess this borrower, what collateral ratio for this wallet?, lending risk for 0x..., what interest rate for this borrower?, should I lend to this wallet?, screen this AI agent, is this agent wallet safe?, agent trust score for 0x..., check the feeder wallet for this agent, can I trust this agent?, route this wallet to onboarding, is this user a beginner?, skip onboarding for this wallet?, or any request to analyze a blockchain wallet address, smart contract, token, or AI agent for risk, behavior, intent, community strength, or trustworthiness. Also use when integrating the ChainAware MCP server into Claude Code, Cursor, ChatGPT, or any MCP-compatible AI agent framework.
License
MIT
Instructions
732 lines in SKILL.md · view on GitHub

Agent Skills spec issues

  • name: "chainaware-behavioral-prediction" does not match folder "behavioral-prediction-mcp"
  • description: longer than 1024 characters
  • body: 732 lines (spec recommends under 500)

Files (91)

  • chainaware-agent-screener.md · .claude/agents/
  • chainaware-agent-trust-screener.md · .claude/agents/
  • chainaware-airdrop-screener.md · .claude/agents/
  • chainaware-aml-scorer.md · .claude/agents/
  • chainaware-cohort-analyzer.md · .claude/agents/
  • chainaware-compliance-screener.md · .claude/agents/
  • chainaware-counterparty-screener.md · .claude/agents/
  • chainaware-credit-scorer.md · .claude/agents/
  • chainaware-defi-advisor.md · .claude/agents/
  • chainaware-fraud-detector.md · .claude/agents/
  • chainaware-gamefi-screener.md · .claude/agents/
  • chainaware-governance-screener.md · .claude/agents/
  • chainaware-lead-scorer.md · .claude/agents/
  • chainaware-lending-risk-assessor.md · .claude/agents/
  • chainaware-ltv-estimator.md · .claude/agents/
  • chainaware-marketing-director.md · .claude/agents/
  • chainaware-onboarding-router.md · .claude/agents/
  • chainaware-platform-greeter.md · .claude/agents/
  • chainaware-portfolio-risk-advisor.md · .claude/agents/
  • chainaware-reputation-scorer.md · .claude/agents/
  • chainaware-rug-pull-detector.md · .claude/agents/
  • chainaware-rwa-investor-screener.md · .claude/agents/
  • chainaware-sybil-detector.md · .claude/agents/
  • chainaware-token-analyzer.md · .claude/agents/
  • chainaware-token-audit-analyst.md · .claude/agents/
  • chainaware-token-launch-auditor.md · .claude/agents/
  • chainaware-token-ranker.md · .claude/agents/
  • chainaware-transaction-monitor.md · .claude/agents/
  • chainaware-trust-scorer.md · .claude/agents/
  • chainaware-upsell-advisor.md · .claude/agents/
  • chainaware-wallet-auditor.md · .claude/agents/
  • chainaware-wallet-marketer.md · .claude/agents/
  • chainaware-wallet-ranker.md · .claude/agents/
  • chainaware-whale-detector.md · .claude/agents/
  • .gitignore
  • AGENTS.md
  • CLAUDE.md
  • LICENSE
  • OPENAI-REGISTRY.md
  • README.md
  • SKILL.md
  • openai.yaml · agents/
  • README.md · assets/
  • logo-large.png · assets/
  • logo-small.png · assets/
  • logo.png · assets/
  • chainaware-eliza-integration.md
  • chainaware-fetchai-integration.md
  • chainaware-agent-screener.json · eliza/characters/
  • chainaware-agent-trust-screener.json · eliza/characters/
  • chainaware-airdrop-screener.json · eliza/characters/
  • chainaware-aml-scorer.json · eliza/characters/
  • chainaware-cohort-analyzer.json · eliza/characters/
  • chainaware-compliance-screener.json · eliza/characters/
  • chainaware-counterparty-screener.json · eliza/characters/
  • chainaware-defi-advisor.json · eliza/characters/
  • chainaware-fraud-detector.json · eliza/characters/
  • chainaware-gamefi-screener.json · eliza/characters/
  • chainaware-governance-screener.json · eliza/characters/
  • chainaware-lead-scorer.json · eliza/characters/
  • …and 31 more

SKILL.md (first lines)

# ChainAware Behavioral Prediction MCP

## What This Skill Does

The **ChainAware Behavioral Prediction MCP** connects any AI agent to a continuously updated
Web3 behavioral intelligence layer: **14M+ wallet profiles** across **8 blockchains**, built from
**1.3 billion+ predictive data points**. It delivers fourteen capabilities via a single MCP endpoint:

1. **Fraud Detection** — predict fraudulent wallet behavior before it happens ([~98% accuracy on ETH](https://chainaware.ai/scam-db))
2. **Batch Fraud Detection** — async batch job for fraud screening large wallet lists; returns `job_id` + `signature`
3. **Behavioral Analysis** — profile wallet intent, risk tolerance, experience, and next likely actions
4. **Batch Behavioral Analysis** — async batch job for behavioral profiling large wallet lists; returns `job_id` + `signature`
5. **Batch Job Status** — poll the progress of any running batch job
6. **Batch Job Results** — retrieve full per-wallet results from a completed or partial batch job
7. **Rug Pull Detection** — forecast whether a smart contract or liquidity pool will rug pull
8. **Credit Score** — crypto credit/trust score (1–9) combining fraud probability and social graph analysis
9. **Token Rank List** — rank tokens by holder community strength across chains and categories
10. **Token Rank Single** — deep-dive into a single token's community quality and top holders
11. **Token Audit** — deep multi-module smart contract audit via async get-or-create pipeline; 8 modules (ownership, liquidity, supply, honeypot, reentrancy, permissions, shadow functions, drainability); aggregate risk score 0–100; supports eth, bsc, base, arbitrum, avalanche, optimism, polygon (lowercase)
12. **Token Audit Results** — poll or retrieve completed token audit; full module breakdown when `audit_status == "complete"`; never present data while still queued or running
13. **Agent Trust Score List** — list ERC-8004 registered AI agents with on-chain trust scores (0–1000); paginated and sortable; use to discover agents or resolve agent_id
14. **Agent Trust Score Single** — full trust profile for a single ERC-8004 agent by `agent_id` + `chain_id`; includes trust score, tier, `wallet_verified`, `owner_address`; hard warning if `wallet_verified == false` or `error` is non-null

Unlike forensic blockchain tools that describe the past, this MCP is **predictive** — it tells your
agent what is *about to happen*.

**MCP Server URL:** `https://prediction.mcp.chainaware.ai/sse`  
**GitHub:** https://github.com/ChainAware/behavioral-prediction-mcp  
**Website:** https://chainaware.ai  
**Pricing / API Key:** https://chainaware.ai/pricing · x402 payment supported  
**Twitter:** https://x.com/ChainAware/  
**LinkedIn:** https://www.linkedin.com/company/chainaware  
**Blog:** https://chainaware.ai/blog  
**Learn:** https://chainaware.ai/learn  
**Examples:** https://github.com/ChainAware/examples  
**Fraud Detection Accuracy:** [98% backtesting verified](https://chainaware.ai/scam-db)  
**Rug Pull Detection Accuracy:** [90.1% backtesting verified](https://chainaware.ai/resources/rugpull-verification)  
**Recognition:** [CB Insights Fraud Prevention Market Map](https://www.cbinsights.com/research/report/the-fraud-prevention-market-map-for-the-ai-era/) (2026) · [BNB Chain AI Landscape](https://x.com/BNBCHAIN/status/1947597551139500419) (2025) · [BNB Chain Kickstart](https://www.bnbchain.org/en/programs/kickstart#services) (2025) · [Google Cloud $250k Grant](https://chainaware.ai/blog/google-cloud-grant/) (2025) · [AWS Fintech Accelerator](https://chainaware.ai/blog/aws-grant/) (2024) · [Safary Club Web3 Growth Landscape](https://x.com/Safaryclub/status/1822983239734329613) (2024)

---

## Capabilities

- **Fraud Detection** — predict fraudulent wallet behavior before it happens ([~98% accuracy on ETH](https://chainaware.ai/scam-db))
- **Batch Fraud Detection** — async batch fraud screening for large wallet lists; fire-and-fetch pattern via `predictive_fraud_batch` → `check_job_status` → `get_job_results`
- **Behavioral Analysis** — profile wallet intent, risk tolerance, experience, and next likely actions across DeFi, NFT, and trading segments
- **Batch Behavioral Analysis** — async batch behavioral profiling for large wallet lists; same fire-and-fetch pattern via `predictive_behaviour_batch` → `check_job_status` → `get_job_results`
- **Rug Pull Detection** — forecast whether a smart contract or liquidity pool will rug pull
- **Credit Score** — crypto credit/trust score (1–9) combining fraud probability and social graph analysis for DeFi lending decisions
- **Token Rank List** — rank tokens by holder community strength across ETH, BNB, BASE, and Solana
- **Token Rank Single** — deep-dive into a specific token's community quality and top holders

---

## When to Use This Skill

- User asks about wallet safety, fraud risk, or suspicious activity
- User wants to screen a wallet, contract, or LP before interacting with it
- User needs AML/compliance checks on a blockchain address
- User wants behavioral profiling or DeFi personalization for a wallet
- User asks about token quality, community strength, or holder analysis
- User is building a DeFi platform, AI agent, launchpad, or compliance tool
- User wants to integrate the ChainAware MCP into their codebase

## When NOT to Use This Skill

- User asks about general blockchain data (balances, transaction history) → use a block explorer
- User wants real-time price data or market cap → use a market data API
- User wants to analyze smart contract code for bugs → use a code auditing tool
- For complex behavioural analysis (deep wallet profiling including fraud signals) → escalate to `chainaware-wallet-auditor` subagent
- For batch screening of many wallets → use batch MCP tools (`predictive_fraud_batch` / `predictive_behaviour_batch`) for large lists, or `chainaware-fraud-detector` subagent for small lists
- For marketing personalization → use `chainaware-wallet-marketer` subagent

---

## Supported Blockchains

| Tool | Networks |
|---|---|
| `predictive_fraud` | ETH, BNB, POLYGON, TON, BASE, TRON, HAQQ |
| `predictive_fraud_batch` | ETH, BNB, POLYGON, TON, BASE, TRON, HAQQ |
| `predictive_behaviour` | ETH, BNB, BASE, HAQQ, SOLANA |
| `predictive_behaviour_batch` | ETH, BNB, BASE, HAQQ, SOLANA |
| `check_job_status` | Network-agnostic (uses job_id + signature) |
| `get_job_results` | Network-agnostic (uses job_id + signature) |
| `predictive_rug_pull` | ETH, BNB, BASE, HAQQ |
| `credit_score` | ETH |
| `token_rank_list` | ETH, BNB, BASE, SOLANA |
| `token_rank_single` | ETH, BNB, BASE, SOLANA |
| `run_token_audit` | eth, bsc, base, arbitrum, avalanche, optimism, polygon *(lowercase)* |
| `get_token_audit_result` | eth, bsc, base, arbitrum, avalanche, optimism, polygon *(lowercase)* |
| `agents_trust_score_list` | Chain-ID-based (ERC-8004 registry) |
| `agents_trust_score_single` | Chain-ID-based (ERC-8004 registry) |

---

## Step-by-Step Workflow

### For wallet fraud screening

1. **Confirm inputs** — wallet address and network. If network is missing, ask.
2. **Call `predictive_fraud`** with the wallet address and network.
3. **Interpret `probabilityFraud`** using the threshold table below.
4. **Scan `forensic_details`** for negative flags (mixer use, sanctioned entities, darknet, etc.).
5. **Report** status, score, and any forensic flags in plain language.

### For behavioral profiling / personalization

1. **Confirm inputs** — wallet address and network.
2. **Call `predictive_behaviour`** with the wallet address and network.
3. **Extract key signals**: `intention.Value` (Prob_Trade/Stake/Bridge/NFT_Buy), `experience.Value`, `categories`, `recommendation`.
4. **Classify the wallet** by dominant category and intent signal.
5. **Generate** personalized recommendations or next-best-action based on the profile.

### For rug pull / contract safety checks

1. **Confirm inputs** — smart contract or LP address and network.
2. **Optionally call `predictive_fraud`** on the *deployer* address first for extra signal.
3. **Call `predictive_rug_pull`** with the contract address.

From ChainAware/behavioral-prediction-mcp, MIT.

Signals

Stars
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Forks
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Open issues
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Last commit
Aug 11, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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chainaware-behavioral-prediction skill. Agent Mart. https://agentmart.dev/skills/chainaware-chainaware-behavioral-prediction (last updated 2026-10-24)