Stablecoin Resilience Classification

VerifiedSafe

Classifies stablecoins to override default resilience sub-factor scores (chainRisk, collateralQuality, custodyModel) when the default inference is incorrect. Useful after adding new stablecoins or auditing existing scores for accuracy.

Sby Skills Guide Bot
Data & AIAdvanced
506/2/2026
Claude Code
#stablecoin#resilience#classification#defi#research

Recommended for

Our review

Researches and classifies stablecoins for resilience sub-factor overrides (chain risk, collateral quality, custody model).

Strengths

  • Systematic process with clear classification rules
  • Parallel research to save time
  • Reduces manual errors in stablecoin assessment

Limitations

  • Depends on quality of web searches and sources found
  • May miss newly added or obscure stablecoins
  • Requires strong DeFi domain knowledge
When to use it

After implementing default resilience types, to correct misclassifications of stablecoins.

When not to use it

When the default inference is already correct for all stablecoins in the tracker.

Security analysis

Safe
Quality score90/100

The skill instructs reading project files, web research, and editing source code. No destructive, exfiltrating, or obfuscated actions. The npm run build command is standard development operation. No risk of compromising safety.

No concerns found

Examples

Classify USDe for resilience overrides
Research and classify the stablecoin USDe for resilience sub-factor overrides (chainRisk, collateralQuality, custodyModel). Identify where the default inference is wrong and propose overrides.
Find stablecoins needing overrides
Identify all stablecoins in our tracker that likely need resilience overrides. Apply the default inference rules and flag candidates based on keywords like 'Solana', 'WBTC', 'Copper', or known-override list (HYUSD, USDe, meUSD, etc.).
Classify custody model of HYUSD
Research HYUSD's custody model. Determine if it is onchain, institutional, or CEX. Use web sources to find where the collateral is held and whether it can be verified on-chain.

name: resilience-classify description: Research and classify stablecoins for resilience sub-factor overrides (chainRisk, collateralQuality, custodyModel). Run after types/defaults are implemented to identify coins needing explicit overrides.

Resilience Classification Skill

Identify stablecoins where the default inference (from backing + governance) is incorrect and apply overrides.

When to Invoke

  • After the resilience types and default inference are implemented
  • When a new stablecoin is added to the tracker
  • When auditing resilience scores for accuracy

Process

Step 1 — Identify candidates

Read all coins from src/lib/stablecoins.ts. For each, apply the default inference rules (see inferResilienceDefaults() in src/lib/report-cards.ts). Flag coins where the default is likely wrong based on:

  • collateral text containing keywords: "Solana", "tBTC", "WBTC", "delta-neutral", "perpetual", "CEX", "off-exchange", "Copper", "Ceffu", "Fireblocks", "bridged"
  • pegMechanism text containing: "Solana", "Bitcoin L2", "not Ethereum", "Tron"
  • contracts[] listing only non-Ethereum chains
  • backing = crypto-backed but collateral text mentions RWAs, bridges, or exotic strategies
  • Coins on this known-override list: HYUSD, USDe, meUSD, USDD, sUSD (Synthetix), USDJ

Step 2 — Research each candidate

For each flagged coin, in parallel:

  • WebFetch official docs for collateral composition, custody arrangement, and chain architecture
  • WebSearch for "{coin name}" stablecoin collateral custody chain to find independent analysis
  • Cross-reference with existing collateral and pegMechanism text fields

Step 3 — Classify

For each coin, determine the correct tier:

| Sub-factor | Question | Tiers | |---|---|---| | chainRisk | Where does the core protocol live and where is collateral held? | ethereum (100), stage1-l2 (66), established-alt-l1 (33), unproven (0) | | collateralQuality | What are the trust assumptions in backing assets? | native (100), eth-lst (66), alt-lst-bridged-or-mixed (33), exotic (0) | | custodyModel | Who holds the collateral and can it be verified on-chain? | onchain (100), institutional (50), cex (0) |

Classification rules:

  • chainRisk: Based on where the protocol's smart contracts and collateral vaults live, NOT where the token is bridged to
  • collateralQuality: For mixed collateral, use the tier of the riskiest significant component (>15% of backing). Stablecoin portions don't count here (handled by dependency risk)
  • custodyModel: If ANY significant portion is held off-chain by a non-institutional custodian, classify as cex
  • When uncertain between two tiers, choose the riskier (lower score) tier

Step 4 — Present findings

For each coin needing an override, present:

## {Name} ({Symbol}) — ID: {id}

### Default inference
- chainRisk: {inferred} — {correct/wrong because...}
- collateralQuality: {inferred} — {correct/wrong because...}
- custodyModel: {inferred} — {correct/wrong because...}

### Proposed overrides
- {field}: {value} — {justification with source URL}

### No override needed
- {fields where default is correct}

Step 5 — Apply

After user approval, edit src/lib/stablecoins.ts to add only the override fields that differ from defaults. Example:

usd("123", "Example", "EX", "crypto-backed", "decentralized", {
  // ... existing fields ...
  chainRisk: "established-alt-l1",
  collateralQuality: "alt-lst-bridged",
}),

Run npm run build to verify.

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