Onchain Analysis Skill for Openclaw

A strategic tool for interpreting blockchain data to identify patterns, anomalies, and fund flows with data-backed evidence.

mzfshark
v2.0.0
Apr 25, 2026
0
1k
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install onchain-analysis

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install onchain-analysis using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Onchain Analysis Skill?

The Onchain Analysis skill empowers AI agents to perform deep-dive investigations into blockchain activity. By leveraging this tool within the Openclaw Skills ecosystem, developers can automate the detection of suspicious wallet behavior and analyze complex contract interactions. It moves beyond simple data retrieval by synthesizing raw transaction histories into actionable risk signals and strategic insights.

This skill is designed for high-stakes environments where understanding the movement of digital assets is critical. Whether monitoring protocol health or tracing insider movements, Onchain Analysis provides a structured framework for data-backed evidence and hypothesis testing, ensuring that every conclusion is rooted in verifiable blockchain records.

Onchain Analysis Skill Use Cases

  • Investigating suspicious wallet or smart contract behavior for potential security risks
  • Mapping complex fund flows to understand asset movement before making investment decisions
  • Analyzing market behavior and detecting potential insider movements or whale activity
  • Monitoring protocol health and identifying liquidity anomalies or unusual contract interactions

How Onchain Analysis Skill Works

  1. Normalize input data by ensuring chain contexts and time windows are explicit and transaction IDs are uniquely identified.
  2. Identify recurring patterns such as periodic withdrawals, deposits, and specific concentration or dispersion of assets.
  3. Detect anomalies including sudden large-volume transfers and interactions with high-volume new counterparties.
  4. Map fund flows from sources to sinks, identifying intermediate hops and specific bridge or aggregator interactions.
  5. Evaluate intent through multiple plausible hypotheses, assigning confidence scores based on available evidence.
  6. Generate action-oriented outputs including risk signals, opportunities, and specific next-check verification steps.

Onchain Analysis Skill Setup

To integrate this capability into your AI agent, ensure you have a compatible runtime for Openclaw Skills. You will need access to blockchain data providers or RPC nodes for the specific chains you wish to analyze.

# Example of adding the onchain-analysis skill to your workspace
openclaw add onchain-analysis

Configure your environment variables with the necessary API keys for transaction indexing services to ensure the skill can fetch the required wallet and contract data.

Onchain Analysis Skill Data Schema & Taxonomy

The skill organizes its analysis using a structured schema to ensure clarity between facts and hypotheses:

Attribute Description Requirement
transactions List of transaction IDs or hashes to be analyzed Required
wallet_data Address labels, balances, and known entities Optional
contract_data Contract address, ABI, and known roles Optional
chain The specific blockchain and timeframe for analysis Optional
insights Synthesized patterns and facts derived from the data Output
risk_signals Indicators of suspicious or high-risk activity Output

Onchain Analysis Skill Advanced Features

  • Multi-hop flow mapping to trace assets through complex paths involving bridges and aggregators
  • Confidence-weighted hypothesis generation to distinguish between facts and probabilistic interpretations
  • Strategic entity labeling to identify known institutional actors versus anonymous wallets
  • Seamless interoperability with other Openclaw Skills for automated financial forensics and reporting

SKILL.md


Loading

Related Openclaw Skills

METADATA

Github Stars: 0
forks: 0

Featured*