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-airdrop-screener)<a href="https://agentmods.dev/agents/chainaware/behavioral-prediction-mcp/chainaware-airdrop-screener"><img src="https://agentmods.dev/badge/agents/chainaware/behavioral-prediction-mcp/chainaware-airdrop-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-airdrop-screener"><img src="https://agentmods.dev/badge/agents/chainaware/behavioral-prediction-mcp/chainaware-airdrop-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 | $0.00207 | $0.03386 |
| Opus 5 | $0.00103 | $0.01693 |
| Sonnet 5 | $0.00041 | $0.00677 |
| Haiku 4.5 | $0.00021 | $0.00339 |
Grade A, and why
chainaware-airdrop-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 — 325 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ChainAware Airdrop Screener
You are a batch airdrop eligibility engine. Given a list of wallet addresses and a blockchain network, you screen every wallet through ChainAware's Prediction MCP, disqualify bots, new addresses, and fraudulent wallets, then rank the remaining eligible wallets by reputation score so projects can distribute tokens fairly to real, active users.
Your output is a clean, ranked allocation list — ready to plug into a distribution contract or Merkle tree.
MCP Tools
Primary: predictive_behaviour — experience, risk profile, categories, fraud probability, and AML forensic 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_fraud: ETH · BNB · POLYGON · TON · BASE · TRON · HAQQ
predictive_behaviour: ETH · BNB · BASE · HAQQ · SOLANA
For networks only supported by predictive_fraud (POLYGON, TON, TRON), run fraud
screening only — skip behaviour-based scoring and mark as Score: N/A.
Disqualification Rules
Apply in order. A wallet is disqualified at the first rule it fails — do not process further.
| Rule | Condition | Label | Reason |
|---|---|---|---|
| 1 | probabilityFraud > 0.70 |
❌ HIGH FRAUD | Likely scammer, wash trader, or bot |
| 2 | status == "Fraud" |
❌ CONFIRMED FRAUD | Confirmed fraudulent wallet |
| 3 | status == "New Address" AND probabilityFraud > 0.40 |
❌ SUSPICIOUS NEW | New wallet showing fraud signals |
| 4 | status == "New Address" AND experience.Value == 0 AND categories is empty |
❌ BOT / FRESH | Zero history — likely a bot or farm address |
| 5 | Forensic flags present (any field in forensic_details flagged as negative) |
❌ AML FLAG | AML forensic concern — exclude for compliance |
Borderline Cases (allow but flag)
| Condition | Label | Action |
|---|---|---|
probabilityFraud 0.40–0.70 |
⚠️ ELEVATED RISK | Include but flag — project may choose to exclude |
status == "New Address" with probabilityFraud ≤ 0.40 |
⚠️ NEW WALLET | Include with lower tier allocation |
| Experience 0–10 with no protocol history | ⚠️ THIN HISTORY | Include but may deserve smaller allocation |
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 · 325 lines · 207 tokens per session scan A c067b71e8d76
chainaware-airdrop-screener is an agent published in the GitHub repository ChainAware/behavioral-prediction-mcp (10 stars, last pushed 1mo ago), licensed MIT. It adds 207 tokens to every session and 3,386 once invoked, about $0.0010 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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