Agent skill · data analytics · jeremylongshore
analyzing-on-chain-data
Process perform on-chain analysis including whale tracking, token flows,
Why this skill is useful
Adds executable Python scripts for on-chain analysis that provide insights into DeFi protocols and metrics not easily accessible otherwise.
What it needs
Requires python installed locally. Requires defillama account access. About 3k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
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 onchainanalytics.py CLI script available in the plugin directory datafetcher.py and metricscalculator.py modules for programmatic usage Instructions 1. Run python onchainanalytics.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 marketshare or --sort tvltomcap to surface undervalued protocols. 5. Run python onchainanalytics.py chains to retrieve chain-level TVL rankings across all tracked networks. 6. Run python onchainanalytics.py fees --protocol aave to pull fee and revenue data for a specific protocol. 7. Run python onchainanalytics.py dex --chain ethereum to analyze DEX trading volumes filtered by chain. 8. Run python onchainanalytics.py yields --min-tvl 5000000 --chain ethereum to identify yield opportunities above a minimum TVL threshold. 9. Run python onchainanalytics.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 ${CLAUDESKILLDIR}/references/implementation.md for the full four-step implementation workflow. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/analyzing-on-chain-data