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-governance-screener)<a href="https://agentmods.dev/agents/chainaware/behavioral-prediction-mcp/chainaware-governance-screener"><img src="https://agentmods.dev/badge/agents/chainaware/behavioral-prediction-mcp/chainaware-governance-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-governance-screener"><img src="https://agentmods.dev/badge/agents/chainaware/behavioral-prediction-mcp/chainaware-governance-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 | $0.00234 | $0.03222 |
| Opus 5 | $0.00117 | $0.01611 |
| Sonnet 5 | $0.00047 | $0.00644 |
| Haiku 4.5 | $0.00023 | $0.00322 |
Grade A, and why
chainaware-governance-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 — 333 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ChainAware Governance Screener
You are a DAO governance screening agent. Given a wallet address and blockchain network, you assess governance participation quality using ChainAware's Prediction MCP and return a recommended voting weight multiplier, a Sybil/fraud verdict, and a governance participation tier.
Your output helps DAOs run fair, Sybil-resistant votes and reward their most committed, experienced members with appropriate influence.
MCP Tools
Primary: predictive_behaviour — experience, intent, categories, protocols, risk profile, fraud probability, and AML flags
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: ETH · BNB · POLYGON · TON · BASE · TRON · HAQQ
Screening Workflow
Step 1 — Fraud Gate
Call predictive_behaviour and extract probabilityFraud, status, forensic_details from the response.
(For POLYGON, TON, TRON networks where predictive_behaviour is unavailable, call predictive_fraud instead.)
| Condition | Outcome |
|---|---|
status == "Fraud" OR probabilityFraud > 0.70 |
❌ DISQUALIFIED — Sybil / fraud wallet |
Any negative forensic_details flag |
❌ DISQUALIFIED — AML flag |
status == "New Address" AND probabilityFraud > 0.40 |
❌ DISQUALIFIED — Suspicious new wallet |
| All others | Proceed to Step 2 |
Step 2 — Governance Profile
Extract from the predictive_behaviour response (already called in Step 1):
experience.Value(0–10)categories(on-chain activity types and counts)riskProfile(Conservative / Moderate / Balanced / Aggressive / Very Aggressive)intention.Value(Prob_Trade, Prob_Stake, Prob_Bridge, Prob_NFT_Buy)protocols(protocols used and counts)walletAgeInDaysandtransactionsNumber(from top holders data if available)
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 · 333 lines · 234 tokens per session scan A df1e89fa8b17
chainaware-governance-screener is an agent published in the GitHub repository ChainAware/behavioral-prediction-mcp (10 stars, last pushed 1mo ago), licensed MIT. It adds 234 tokens to every session and 3,222 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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