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".
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill analyzing-on-chain-data59
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Report generation workflow
Report directory
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Multiple subcommands
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Chains subcommand used
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Trends subcommand used
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Fees subcommand used
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onchain_analytics.py script used
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Market summary section
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Chain TVL section
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Trending protocols section
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Actionable insights
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run_log.sh is executable shell
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Without context: $0.9613 · 3m 19s · 31 turns · 28 in / 11,563 out tokens
With context: $1.2855 · 3m 10s · 46 turns · 4,956 in / 10,580 out tokens
Yield analysis with filters
yields subcommand used
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--chain filter applied
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--min-tvl filter applied
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JSON format for raw output
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Cache cleared
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onchain_analytics.py script used
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yields_raw.json produced
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yield_report.md produced
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commands.sh is valid shell
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Top 15 limit
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Without context: $0.3390 · 1m 24s · 18 turns · 19 in / 5,000 out tokens
With context: $0.6923 · 2m 18s · 30 turns · 800 in / 7,207 out tokens
Protocol metrics programmatic analysis
DataFetcher import
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MetricsCalculator import
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fetch_protocols called
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Lending category filter
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calculate_market_share called
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calculate_tvl_to_mcap called
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Ranked by tvl_to_mcap
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lending_comparison.json written
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vars() conversion used
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Actionable insight in report
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lending_report.md produced
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Without context: $0.8065 · 2m 33s · 33 turns · 2,011 in / 8,890 out tokens
With context: $0.7784 · 2m 13s · 30 turns · 11,769 in / 6,747 out tokens
Table of Contents
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