
On-Chain Data Analysis
FreeEfficiently analyze blockchain data for DeFi insights.
Free · Opens the source repo
What On-Chain Data Analysis does
The On-Chain Data Analysis skill provides a streamlined way to analyze various metrics related to decentralized finance (DeFi) protocols. By leveraging the DeFiLlama API, this skill allows users to access critical data such as total value locked (TVL), fee revenue, decentralized exchange (DEX) volumes, and yield opportunities. It is particularly useful for DeFi researchers, protocol analysts, and yield farmers who require programmatic access to on-chain analytics without the need to write complex queries.
With this skill, users can execute a series of commands to retrieve and filter data based on specific criteria. For instance, users can rank protocols by TVL, filter results by category or blockchain, and sort by alternative metrics to identify undervalued opportunities. The ability to export results in JSON or CSV format further enhances its utility, allowing for easy integration with other tools or for further analysis in spreadsheet applications.
The skill is designed to be user-friendly, requiring only a basic setup with Python and access to the DeFiLlama API. It offers a comprehensive suite of commands that cover a wide range of analytical needs, from daily overviews of DeFi activity to in-depth analysis of specific protocols. This makes it an invaluable tool for anyone looking to gain insights into the rapidly evolving DeFi landscape.
In summary, the On-Chain Data Analysis skill simplifies the process of gathering and analyzing blockchain data, making it accessible to both seasoned analysts and newcomers to the DeFi space. Its straightforward command-line interface and reliance on established APIs ensure that users can quickly obtain the information they need to make informed decisions in their crypto endeavors.
When to use it
Use this skill when you need to analyze blockchain data for DeFi metrics, such as TVL or yield opportunities.
When not to use it
This skill may not be suitable for users looking for real-time trading execution or complex financial modeling beyond basic analytics.
What you can build with it
Daily DeFi Overview
Run a series of commands to get a snapshot of the top protocols by TVL and chain rankings.
Research a Lending Protocol
Analyze lending protocols by TVL-to-market-cap ratio and pull fee data for specific protocols.
Identify High-TVL Yield Opportunities
Find yield pools on Ethereum with significant TVL and export the results for further analysis.
How to install On-Chain Data Analysis
View source1. Install with the skills CLI
npx skills add jeremylongshore/claude-code-plugins-plus-skills/analyzing-on-chain-data --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by jeremylongshoreAnalyzing 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
requestslibrary installed - DeFiLlama API access (free, no key required for most endpoints)
- Optional: CoinGecko API key for supplementary token price data
onchain_analytics.pyCLI script available in the plugin directorydata_fetcher.pyandmetrics_calculator.pymodules for programmatic usage
Instructions
- Run
python onchain_analytics.py protocolsto retrieve the top DeFi protocols ranked by total value locked (TVL). - Filter protocol results by category using
--category lending,--category dex, or--category "liquid staking"to narrow the scope. - Filter by chain with
--chain ethereumor--chain arbitrumto isolate chain-specific protocol data. - Sort results by alternative metrics using
--sort market_shareor--sort tvl_to_mcapto surface undervalued protocols. - Run
python onchain_analytics.py chainsto retrieve chain-level TVL rankings across all tracked networks. - Run
python onchain_analytics.py fees --protocol aaveto pull fee and revenue data for a specific protocol. - Run
python onchain_analytics.py dex --chain ethereumto analyze DEX trading volumes filtered by chain. - Run
python onchain_analytics.py yields --min-tvl 5000000 --chain ethereumto identify yield opportunities above a minimum TVL threshold. - Run
python onchain_analytics.py trends --threshold 5to detect protocols with significant TVL changes (threshold is percentage). - Export results in JSON or CSV format using
--format jsonor--format csvand 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
- Chain TVL rankings showing aggregate locked value per network
- Fee and revenue reports per protocol with daily/weekly/monthly breakdowns
- DEX volume tables with per-chain and per-DEX breakdowns
- Yield opportunity listings filtered by minimum TVL and chain, including APY and pool details
- Trending protocol alerts showing TVL percentage changes above the configured threshold
- Stablecoin market cap summaries
- JSON (
output.json) or CSV (output.csv) export files for programmatic consumption
Error Handling
| Error | Cause | Solution |
|---|---|---|
Request timeout | DeFiLlama API slow or unreachable | Wait and retry; check for outages; use cached data if available |
Protocol not found: invalid-name | Protocol slug does not match DeFiLlama database | Run python onchain_analytics.py protocols to find the exact slug; slugs are case-sensitive |
No data returned for query | Filter too restrictive or data unavailable | Remove filters and retry; verify the category or chain exists; try a broader time range |
TVL data unavailable for some protocols | New protocols or data collection gaps | Check DeFiLlama directly; data typically appears within 24 hours of listing |
Data may be stale (last updated: X hours ago) | Local cache not refreshed | Clear cache with rm ~/.onchain_analytics_cache.json; use --verbose to check cache status |
Showing top 50 of 1000+ protocols | Output truncated for readability | Use --limit to increase count or --format json for full untruncated data |
UnicodeEncodeError | Terminal encoding mismatch | Use --format json for safe output or set LANG=en_US.UTF-8 |
Examples
Daily DeFi Overview
python onchain_analytics.py protocols --limit 20
python onchain_analytics.py chains
python onchain_analytics.py trends
Produces a snapshot of the top 20 protocols by TVL, all chain rankings, and any protocols trending above the default threshold.
Research a Lending Protocol
python onchain_analytics.py protocols --category lending --sort tvl_to_mcap
python onchain_analytics.py fees --protocol aave
Ranks all lending protocols by TVL-to-market-cap ratio (identifying potentially undervalued protocols), then pulls detailed fee and revenue data for Aave.
Find High-TVL Yield Opportunities on Ethereum
python onchain_analytics.py yields --min-tvl 10000000 --chain ethereum --limit 50 # 10000000 = 10M limit
Returns up to 50 yield pools on Ethereum with at least $10M in TVL, sorted by APY. Export with --format csv > yields.csv for spreadsheet analysis.
Resources
- DeFiLlama API Documentation -- primary data source for TVL, fees, yields, and DEX volumes
- DeFiLlama Status Page -- check API availability and outage reports
- CoinGecko API -- supplementary token price and market cap data
- Dune Analytics -- custom SQL queries against on-chain data for deeper analysis
- The Graph -- decentralized indexing protocol for querying blockchain data via GraphQL
Frequently asked questions about On-Chain Data Analysis
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