stablecoin-analysis
Methodology playbook for analyzing stablecoin volume, supply, holders, and geographic usage on Allium — USDC, USDT, DAI, USDS, RLUSD, USDG, JPYC, and other fiat/crypto/ algorithmic-backed stablecoins. Use whenever a question touches stablecoin transfer volume, circulating supply, wallet/holder counts, geo splits, or cross-chain deployments — even if the user just names a specific stablecoin, asks for "adoption" or "usage" numbers, or asks to compare volume to a chart/number they already have. Covers the raw-vs-adjusted volume distinction, chain-specific double-counting mechanics, and address/case-sensitivity gotchas that come up repeatedly before you write the SQL.
Install
With your agent
Install OMGSkills skill "allium-labs/allium-claude-plugin:skills/stablecoin-analysis" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/allium-labs/allium-claude-plugin /tmp/allium-claude-plugin && ln -s /tmp/allium-claude-plugin/skills/stablecoin-analysis ~/.claude/skills/stablecoin-analysisFrom README
Stablecoin Analysis The single most consequential decision in any stablecoin volume question is raw vs. adjusted volume — get that wrong and every downstream number is off by 5-20x. Read this before writing SQL. Raw volume overstates organic activity — use adjusted Per-transfer tables include CEX-internal transfers, DeFi-protocol internal movements, MEV, and wash flows. SUM(usdamount) on a raw transfers table answers "how much value moved," not "how much real economic activity happened" — and the two can differ by an order of magnitude. For real adoption/ analysis, use the entity-adjusted volume columns (look for isadjustedvolume, isinorganicsender/isinorganicreceiver, ismevtransfer style flags, or a pre-aggregated entity-adjusted metrics table) rather than raw SUM. If a user shares a chart or number they already trust and your raw-volume query comes back 5-20x higher, that's usually not a bug in your query — it's the raw-vs-adjusted gap.
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