k3-blockchain-agent_skill

Overview

This skill builds end-to-end blockchain analysis workflows on K3 from plain-language requests to deployed automations that fetch on-chain data, analyze it with AI, and deliver results via email, Telegram, or Slack. It guides you through data discovery, testing, workflow generation, deployment, and verification so you get reliable, scheduled DeFi or crypto reports and alerts. Use it to turn requests like “monitor this wallet” or “daily pool report” into running automations.

How this skill works

The skill inspects the user’s intent (data target, chain, schedule, analysis, delivery) and discovers available team data integrations via the K3 MCP. It builds a minimal test workflow to verify data sources, iterates conversationally with the K3 orchestrator using generateWorkflow/editGeneratedWorkflow, and then deploys and verifies the full workflow with executeWorkflow and run checks. The process emphasizes testing data fetches first, choosing the best K3 read function (Read Graph, Read Smart Contract, Read Market Data, etc.), and validating end-to-end delivery.

When to use it

• Create scheduled DeFi reports or dashboards (daily, hourly, on-chain event triggers)
• Monitor wallets, token balances, pool metrics, or NFT collections
• Set up anomaly or threshold alerts for price, TVL, or transfers
• Automate protocol monitoring or smart contract watchlists
• Build automated trading signals or conditional actions tied to on-chain data

Best practices

• Always verify available team integrations with listTeamMcpServerIntegrations() before designing the workflow
• Start with a minimal test workflow (trigger + one data fetch) and run it with executeWorkflow to confirm data shape
• Prefer the most reliable data source available (TheGraph subgraph, protocol API, or direct contract reads) for the metric you need
• Provide exact addresses, API keys, delivery handles, and schedule preferences—don’t guess user values
• Iterate via the orchestrator’s conversational flow and set deployWorkflow:false until you’ve reviewed outputs

Example use cases

• Daily Uniswap pool performance summary emailed to the team with TVL, volume, and liquidity changes
• Telegram alerts when a watched wallet transfers > $100k or an unusual token balance change occurs
• Hourly token price and volatility report posted to a Slack channel for trading ops
• NFT collection tracker that sends floor price and rare trait alerts
• Automated DeFi monitor that performs on-chain checks and runs an AI summary before sending a report