Chain Ecosystem Analysis
Produce a comprehensive overview of a blockchain ecosystem by combining chain-level metrics with protocol, bridge, stablecoin, and user data.
Workflow
Step 1 - Resolve the chain entity
If the chain slug is unknown or ambiguous, resolve it first.
defillama:resolve_entity
entity_type: "chain"
name: "<user-provided name>"Step 2 - Chain-level metrics
Fetch aggregate TVL, fees, revenue, DEX volume, and trends.
defillama:get_chain_metrics
chain: "<slug>"Key fields: tvl_base, chain_fees_1d, chain_revenue_1d, app_fees_1d, volume_dexs_1d, tvl_base_7d_pct_change, tvl_base_30d_pct_change.
Step 3 - Top protocols on the chain
Identify the largest protocols by TVL on this chain.
defillama:get_protocol_metrics
chain: "<slug>"Step 4 - Bridge flows
Measure capital entering and leaving the chain.
defillama:get_bridge_flows
chain: "<slug>"Positive net flow = capital inflow (bullish). Negative = outflow.
Step 5 - Stablecoin supply
Assess stablecoin liquidity available on the chain.
defillama:get_stablecoin_supply
chain: "<slug>"Step 6 - User activity
Fetch active addresses and transaction counts.
defillama:get_user_activity
chain: "<slug>"Output Format
Present the report with these sections in order:
- Chain Overview - Summary paragraph: what the chain is known for, current positioning in the market.
- Key Metrics - Table of TVL, fees, revenue, DEX volume, and percentage changes.
- Top Protocols - Top 5-10 protocols by TVL with category and TVL.
- Bridge Activity - Net flows, top bridges, inflow vs outflow breakdown.
- Stablecoin Liquidity - Total stablecoin supply on chain, top stablecoins, and trend direction.
- User Activity - Active addresses, transaction counts, growth trends.
Tips
- Rising stablecoin supply + positive bridge flows = capital accumulating on chain (bullish signal).
- Compare chain metrics to the previous period to identify momentum.
- If a single protocol dominates TVL (>50%), note the concentration risk.
- DEX volume relative to TVL indicates capital efficiency.
- Use
start_date/end_datefor custom date ranges when analyzing specific periods (e.g.,start_date: "2025-01-01", end_date: "2025-03-31").