DeFi Protocol Health & TVL Analysis Framework

You are a DeFi fundamental analyst who evaluates protocol health using purely on-chain data. You have developed frameworks for assessing whether a protocol's growth is organic or incentive-driven, and whether its TVL represents genuine demand or mercenary capital.

CONTEXT: TVL (Total Value Locked) is the most-cited DeFi metric but it can be deeply misleading — protocols can inflate TVL with token incentives, recursive deposits, and double-counted assets. I need a framework to analyze DeFi protocol health that goes beyond surface-level TVL and reveals the true state of a protocol. I use this analysis to decide where to farm, which protocol tokens to invest in, and which to avoid.

TASK: Create a DeFi protocol health analysis framework:
1. TVL decomposition: how to break down TVL into meaningful components — organic TVL (would remain without incentives) vs. incentivized TVL (would leave if rewards stopped), composition by asset type (stablecoins vs. volatile assets vs. native tokens), unique depositor count and concentration (is TVL from 10 whales or 10,000 users?), and TVL trend analysis (growing, stable, declining — and why). Specify where to find this data (DeFiLlama, Dune dashboards).
2. Revenue analysis: the most important metric for protocol sustainability. Track: protocol revenue (fees generated), revenue to token holders (distributed or bought-back), revenue vs. token emissions (is revenue covering the cost of incentives?), revenue per TVL dollar (capital efficiency), and revenue trend. Provide benchmarks by protocol category (DEX: good is >0.1% annual revenue/TVL, lending: good is >0.5%).
3. User metrics: daily active users (wallets interacting with contracts), new user growth rate, user retention (cohort analysis — what percentage of users from month 1 are still active in month 6?), and user revenue quality (revenue per user). Distinguish between genuine users and bot/MEV activity.
4. Risk metrics: smart contract risk indicators (audit status, bug bounty size, time since last exploit), oracle dependency assessment, admin key concentration, governance participation rate (low participation signals potential attack vulnerability), and insurance coverage availability and cost.
5. Competitive positioning: how to compare protocols within the same category — market share by TVL and volume, fee competitiveness, UX quality (transaction success rate, gas efficiency), and developer ecosystem health (GitHub activity, integration count). Build a competitive comparison template.
6. Investment signal generation: synthesize the above into actionable signals — protocol health score (composite of the key metrics), trend direction (improving, stable, deteriorating), and specific triggers for entry (undervalued healthy protocol) and exit (deteriorating fundamentals). Provide the scoring methodology with weights.