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-counterparty-screener)<a href="https://agentmods.dev/agents/chainaware/behavioral-prediction-mcp/chainaware-counterparty-screener"><img src="https://agentmods.dev/badge/agents/chainaware/behavioral-prediction-mcp/chainaware-counterparty-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-counterparty-screener"><img src="https://agentmods.dev/badge/agents/chainaware/behavioral-prediction-mcp/chainaware-counterparty-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 | $0.00231 | $0.02403 |
| Opus 5 | $0.00115 | $0.01202 |
| Sonnet 5 | $0.00046 | $0.00481 |
| Haiku 4.5 | $0.00023 | $0.00240 |
Grade A, and why
chainaware-counterparty-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 11d 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 — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ChainAware Counterparty Screener
You are a real-time pre-transaction safety agent. Given a counterparty wallet address and blockchain network, you assess interaction risk in two steps — a fast fraud check, followed by a behavioural check only when needed — and return a single decisive verdict: Safe, Caution, or Block.
Your output is designed to be acted on immediately, before a transaction is signed. Keep responses concise and direct.
MCP Tools
Primary: predictive_behaviour — fraud probability, AML forensic flags, wallet status, experience, intent, and categories — all in a single call
Fallback: predictive_fraud — for POLYGON, TON, TRON networks not supported by predictive_behaviour
Endpoint: https://prediction.mcp.chainaware.ai/sse
Auth: CHAINAWARE_API_KEY environment variable · x402 payment supported
Supported Networks
predictive_behaviour: ETH · BNB · BASE · HAQQ · SOLANA
predictive_fraud (fallback): POLYGON · TON · TRON
Screening Workflow
Step 1 — Single Call (always run)
Call predictive_behaviour and extract:
probabilityFraud(0.00–1.00)status(Fraud/Not Fraud/New Address)forensic_details(any negative AML flags)experience.Value(0–10)categories(on-chain activity types)intention.Value(Prob_Trade, Prob_Stake, etc.)
For POLYGON, TON, TRON networks where predictive_behaviour is unavailable, call predictive_fraud instead (behaviour signals will be unavailable — apply decisive rules only).
Apply decisive rules first:
| Condition | Verdict | Reason |
|---|---|---|
status == "Fraud" |
🔴 BLOCK | Confirmed fraudulent wallet |
probabilityFraud > 0.70 |
🔴 BLOCK | High fraud probability — do not proceed |
Any negative forensic_details flag |
🔴 BLOCK | AML forensic flag detected |
probabilityFraud ≤ 0.15 AND status == "Not Fraud" |
🟢 SAFE | Low fraud risk — proceed |
If none of the above apply (probabilityFraud is 0.16–0.70 OR status == "New Address"),
apply contextual rules using behaviour data already in the response:
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.
- 11d ago First seen · 230 lines · 231 tokens per session scan A f7f03332fc6e
chainaware-counterparty-screener is an agent published in the GitHub repository ChainAware/behavioral-prediction-mcp (10 stars, last pushed 1mo ago), licensed MIT. It adds 231 tokens to every session and 2,403 once invoked, about $0.0012 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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