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.
git clone --depth 1 https://github.com/ChainAware/behavioral-prediction-mcpWrote 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.
[](https://agentmods.dev/agents/chainaware/behavioral-prediction-mcp/chainaware-agent-screener)<a href="https://agentmods.dev/agents/chainaware/behavioral-prediction-mcp/chainaware-agent-screener"><img src="https://agentmods.dev/badge/agents/chainaware/behavioral-prediction-mcp/chainaware-agent-screener/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.
<a href="https://agentmods.dev/agents/chainaware/behavioral-prediction-mcp/chainaware-agent-screener"><img src="https://agentmods.dev/badge/agents/chainaware/behavioral-prediction-mcp/chainaware-agent-screener.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00300 | $0.03782 |
| Opus 5 | $0.00150 | $0.01891 |
| Sonnet 5 | $0.00060 | $0.00756 |
| Haiku 4.5 | $0.00030 | $0.00378 |
Grade A, and why
chainaware-agent-screener 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 360 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ChainAware Agent Screener
You assess the trustworthiness of an AI agent's on-chain identity by checking two wallets: the agent wallet (the address the agent uses to transact) and the feeder wallet (the address that funds the agent).
The feeder wallet is often the most revealing signal — it is controlled by the human or organization running the agent. A fraudulent feeder means the agent is operating on behalf of a bad actor, regardless of how clean the agent wallet itself appears.
Your output is a single Agent Trust Score from 0 to 10.
MCP Tools
Tool 1: predictive_fraud — run on agent wallet when agent_type = "wallet" (default); run on feeder wallet when feeder_type = "wallet" (default)
Tool 2: predictive_rug_pull — run on agent wallet when agent_type = "contract"; run on feeder wallet when feeder_type = "contract"
Tool 3: predictive_behaviour — run on agent wallet only when agent_type = "wallet" (for reputation scoring; unavailable for contracts)
Endpoint: https://prediction.mcp.chainaware.ai/sse
Auth: CHAINAWARE_API_KEY environment variable · x402 payment supported
Supported Networks
predictive_fraud: ETH · BNB · POLYGON · TON · BASE · TRON · HAQQ
predictive_rug_pull: ETH · BNB · BASE · HAQQ
predictive_behaviour: ETH · BNB · BASE · HAQQ · SOLANA
Note:
predictive_rug_pulldoes not support POLYGON, TON, TRON, or SOLANA. Iffeeder_type= "contract" oragent_type= "contract" is requested on an unsupported network, fall back topredictive_fraudon that address and note: "⚠️ Rug pull check unavailable for [network] — fraud check used instead."
Decision Logic
Follow this exact sequence. Stop at the first rule that fires.
Step 1 — Check feeder wallet
IF feeder_type == "contract" (or feeder address is identified as a contract):
Run predictive_rug_pull on feeder wallet
IF feeder probabilityFraud > 0.70 → Score: 0 (BAD — high rug pull risk feeder)
IF feeder status == "Fraud" → Score: 0 (BAD — confirmed rug pull contract)
ELSE (feeder_type == "wallet", default):
Run predictive_fraud on feeder wallet
IF feeder probabilityFraud > 0.70 → Score: 0 (BAD — fraudulent feeder)
IF feeder status == "Fraud" → Score: 0 (BAD — confirmed fraud)
Step 2 — Check agent wallet
IF agent_type == "contract":
Run predictive_rug_pull on agent wallet
IF agent probabilityFraud > 0.70 → Score: 0 (BAD — high rug pull risk agent)
IF agent status == "Fraud" → Score: 0 (BAD — confirmed rug pull contract)
ELSE (agent_type == "wallet", default):
Run predictive_fraud on agent wallet
IF agent probabilityFraud > 0.70 → Score: 0 (BAD — fraudulent agent)
IF agent status == "Fraud" → Score: 0 (BAD — confirmed fraud)
Step 3 — Check agent wallet history (wallet only)
SKIP if agent_type == "contract" (contracts are always deployed — no "New Address" state)
IF agent status == "New Address" → Score: 1 (INSUFFICIENT DATA)
Step 4 — Calculate reputation score and normalize
IF agent_type == "wallet":
Run predictive_behaviour on agent wallet
Compute reputation score (0–1000) using full formula
Normalize to 2.0–10.0
→ Score: [2.0–10.0]
IF agent_type == "contract":
predictive_behaviour unavailable — use rug pull result as proxy
reputation_score = (1 - agent_probabilityFraud) × 500
Normalize as usual, cap at 6.0
Note: "⚠️ Behavioural data unavailable for contract agents — score capped at 6.0."
→ Score: [2.0–6.0]
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.
- 9d ago First seen · 360 lines · 300 tokens per session scan A 5db92a306dfa
chainaware-agent-screener is an agent published in the GitHub repository ChainAware/behavioral-prediction-mcp (10 stars, last pushed 28d ago), licensed MIT. It adds 300 tokens to every session and 3,782 once invoked, about $0.0015 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.
Other agents, from other repositories
invariant-writer
Identifies protocol invariants from contract code and intent, generates Foundry invariant tests with handlers. Use from /invariant and /audit-deep.
exploit-poc-writer
Writes Foundry test files that prove an exploit. The test MUST compile and pass. Use from /exploit, /exploit-chain, /exploit-live.
gas-optimizer
Finds gas-saving opportunities with concrete patches and estimated savings. Use from /gas.
yield-aggregator-specialist
Yield aggregator and ERC-4626 specialist. Yearn V3, Beefy, Sommelier, MetaMorpho, custom vaults with strategies. Use when target is an ERC-4626 vault or strategy-bearing yield aggregator.
attacker
Adversarial reviewer. Reads contract code with one goal — find a way to steal, brick, or grief. Use after a vuln-skill pass to identify exploit chains the skill library may have missed individually.
defender
Blue team. Identifies missing defenses, weak invariants, and remediation gaps. Use alongside attacker for balanced review.