OnChain Analysis

Interpret blockchain data strategically; identify patterns, anomalies, and flows with data-backed evidence and explicit uncertainty.

SKILL: onchain-analysis

Purpose

Interpret blockchain data strategically: identify patterns, detect anomalies, map flows, and surface risk signals — data-backed only.

When to Use

• Wallet/contract behavior seems suspicious or unclear
• You need to understand fund flows before a decision
• Investigating market behavior, insider movement, or protocol health

Inputs

• wallet_data (optional): addresses + labels + balances
• contract_data (optional): contract address + ABI/artifacts + known roles
• transactions (required): tx list or tx ids/hashes
• chain (optional): chain + timeframe

Steps

1. Normalize inputs:
   • ensure chain/time window is explicit
   • ensure transactions are uniquely identified
2. Identify patterns:
   • recurring counterparties
   • periodic deposits/withdrawals
   • concentration and dispersion patterns
3. Detect anomalies:
   • sudden large transfers
   • new counterparties with high volume
   • unusual contract interactions
4. Map flows:
   • sources → sinks
   • intermediate hops
   • aggregator/bridge interactions (label as such)
5. Evaluate intent as hypotheses:
   • propose 1–3 plausible explanations
   • attach confidence and what evidence would change it
6. Produce action-oriented output:
   • risk signals
   • what to verify next

Validation

• Include tx hashes / block references when possible.
• Distinguish facts from hypotheses.
• If data is incomplete, state the missing pieces explicitly.

Output

• insights (facts + patterns)
• risk_signals
• opportunities (only if supported by data)
• hypotheses (with confidence)
• next_checks

Safety Rules

• Data-backed only; no “mind reading” claims.
• Do not assist illicit activity or evasion.

Example

Input: 200 txs for one wallet over 30 days. Output: “High concentration into 2 addresses; one new counterparty accounts for 70% volume; verify entity labels + bridge usage.”