Notre avis
Recherche et classifie les stablecoins pour les surcharges des sous-facteurs de résilience (risque de chaîne, qualité du collatéral, modèle de garde).
Points forts
- Processus systématique avec des règles de classification claires
- Recherche parallèle pour gagner du temps
- Réduit les erreurs manuelles dans l'évaluation des stablecoins
Limites
- Dépend de la qualité des recherches web et des sources trouvées
- Peut manquer des stablecoins récemment ajoutés ou obscurs
- Nécessite une bonne connaissance du domaine DeFi
Après avoir implémenté les types par défaut de résilience, pour corriger les classifications erronées des stablecoins.
Lorsque l'inférence par défaut est déjà correcte pour tous les stablecoins du suivi.
Analyse de sécurité
SûrThe 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.
Aucun point d'attention détecté
Exemples
Research and classify the stablecoin USDe for resilience sub-factor overrides (chainRisk, collateralQuality, custodyModel). Identify where the default inference is wrong and propose 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.).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:
collateraltext containing keywords: "Solana", "tBTC", "WBTC", "delta-neutral", "perpetual", "CEX", "off-exchange", "Copper", "Ceffu", "Fireblocks", "bridged"pegMechanismtext containing: "Solana", "Bitcoin L2", "not Ethereum", "Tron"contracts[]listing only non-Ethereum chainsbacking=crypto-backedbut 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:
WebFetchofficial docs for collateral composition, custody arrangement, and chain architectureWebSearchfor"{coin name}" stablecoin collateral custody chainto find independent analysis- Cross-reference with existing
collateralandpegMechanismtext 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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