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llama-analyst

Identify undervalued DeFi protocols using TVL, revenue, and price metrics.

7|Updated Jan 14, 2026
Search Tags:#analytics#screening#cross-chain#defi#revenue#tvl#macro-flows
One-click install
npx skills add https://github.com/dreamineering/meme-times --skill llama-analyst
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llama-analyst
Source: https://github.com/dreamineering/meme-times/tree/main/.claude/skills/llama-analyst
Command: npx skills add https://github.com/dreamineering/meme-times --skill llama-analyst

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

DeFi fundamentals and cross-chain analytics are often scattered across multiple sources, making it hard to identify undervalued protocols or build data-driven theses. This Skill consolidates DefiLlama-style data on TVL, revenue, and token-price signals to help you screen sectors, compare ecosystems, and run rigorous crypto research.

Core Features & Use Cases

  • Protocol screening and ranking by TVL, revenue, price, and efficiency metrics to spot undervalued or overperforming protocols.
  • Sector and ecosystem analytics to compare DEXs, perps, lending, LSDs, and restaking across chains.
  • Flow and macro views to map capital movements and inform meme/degen activity sizing with strong fundamentals.
  • Output formats include ranked tables, concise summaries, and checklists that codify thesis criteria.

Quick Start

Identify the top undervalued DeFi protocols using current TVL and revenue signals to generate a data-driven fundamentals report.

Frequently Asked Questions about llama-analyst

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I identify undervalued DeFi protocols using TVL and revenue data?▼

You can screen DeFi protocols by ranking their TVL, revenue, and price performance metrics using data sourced from DefiLlama and Token Terminal. This approach highlights overperforming or undervalued assets to build data-backed investment theses.

What is the best way to compare DeFi ecosystems across multiple chains?▼

The best way to compare cross-chain DeFi ecosystems is by mapping macro capital movements and analyzing sector metrics like TVL for DEXs, perps, and lending. This flow analysis reveals where capital is migrating across chains.

Can I use Dune Analytics data to screen DeFi sectors like LSDs and restaking?▼

Yes, you can screen DeFi sectors like LSDs and restaking using Dune Analytics data alongside DefiLlama. The Skill consolidates these sources to compare ecosystem fundamentals and rank protocol efficiency metrics.

How do I generate a data-driven investment thesis for crypto protocols?▼

You generate a data-driven investment thesis by codifying protocol screening criteria into checklists and concise summaries from multi-source validated data. This turns scattered DeFi fundamentals into actionable, ranked insights.

Does this approach work for sizing meme and degen activity with strong fundamentals?▼

Yes, this approach works for sizing meme and degen activity by analyzing macro DeFi flows and strong fundamentals. It uses cross-chain capital movement data to inform allocation sizing for higher risk activities.

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