analyzing-on-chain-data

name	analyzing-on-chain-data
description	Process perform on-chain analysis including whale tracking, token flows, and network activity. Use when performing crypto analysis. Trigger with phrases like "analyze crypto", "check blockchain", or "monitor market".
allowed-tools	Read, Write, Edit, Grep, Glob, Bash(crypto:onchain-*)
version	1.28.0
author	Jeremy Longshore <[e-mail]>
license	MIT
tags	["crypto","monitoring","analyzing-on"]
compatibility	Designed for Claude Code, also compatible with Codex and OpenClaw

Analyzing On-Chain Data

Overview

Analyze DeFi protocol metrics, chain-level TVL, fee revenue, DEX volumes, yield opportunities, and stablecoin market caps using DeFiLlama as the primary data source. Designed for DeFi researchers, protocol analysts, and yield farmers who need programmatic access to on-chain analytics without writing custom subgraph queries.

Prerequisites

• Python 3.8+ with requests library installed
• DeFiLlama API access (free, no key required for most endpoints)
• Optional: CoinGecko API key for supplementary token price data
• onchain_analytics.py CLI script available in the plugin directory
• data_fetcher.py and metrics_calculator.py modules for programmatic usage

Instructions

1. Run python onchain_analytics.py protocols to retrieve the top DeFi protocols ranked by total value locked (TVL).
2. Filter protocol results by category using --category lending, --category dex, or --category "liquid staking" to narrow the scope.
3. Filter by chain with --chain ethereum or --chain arbitrum to isolate chain-specific protocol data.
4. Sort results by alternative metrics using --sort market_share or --sort tvl_to_mcap to surface undervalued protocols.
5. Run python onchain_analytics.py chains to retrieve chain-level TVL rankings across all tracked networks.
6. Run python onchain_analytics.py fees --protocol aave to pull fee and revenue data for a specific protocol.
7. Run python onchain_analytics.py dex --chain ethereum to analyze DEX trading volumes filtered by chain.
8. Run python onchain_analytics.py yields --min-tvl 5000000 --chain ethereum to identify yield opportunities above a minimum TVL threshold.
9. Run python onchain_analytics.py trends --threshold 5 to detect protocols with significant TVL changes (threshold is percentage).
10. Export results in JSON or CSV format using --format json or --format csv and redirect to file for downstream analysis.

See ${CLAUDE_SKILL_DIR}/references/implementation.md for the full four-step implementation workflow.

Output

• Protocol rankings table with name, TVL, market share percentage, and TVL-to-market-cap ratio