skills/auralshin/agent-skills/defi-yield-strategy-designer

defi-yield-strategy-designer

SKILL.md

DeFi Yield Strategy Designer

Purpose

Design diversified yield strategies that balance return targets with liquidity, drawdown tolerance, and protocol risk.

Use this skill when

  • The user asks for strategy ideas across staking, lending, LPs, and vaults.
  • The user wants allocation weights under explicit risk constraints.
  • The user wants rebalance triggers and downside playbooks.

Workflow

  1. Capture constraints:
    • Capital size and base currency
    • Acceptable drawdown
    • Liquidity needs
    • Chain/protocol restrictions
  2. Choose candidate archetypes from references/strategy-archetypes.md.
  3. For each candidate, score risk/return and run stress scenarios from references/stress-framework.md.
  4. Build allocation proposal with rebalancing and risk limits.
  5. Return a decision-ready plan with explicit assumptions.

Rules

  • Distinguish base yield from token incentive yield.
  • Penalize strategies with high mercenary-capital dependency.
  • Include a no-incentive yield floor estimate.
  • Reference defi-risk-evaluator output if protocol-level risk scoring is needed.

Required output format

{
  "constraints": {
    "capital_usd": 0,
    "target_apy": 0,
    "max_drawdown_pct": 0,
    "liquidity_needs": "daily|weekly|monthly",
    "chain_constraints": ["string"]
  },
  "candidate_strategies": [
    {
      "name": "string",
      "allocation_pct": 0,
      "expected_apy_base": 0,
      "expected_apy_incentives": 0,
      "yield_floor_apy": 0,
      "key_risks": ["string"],
      "stress_case_apy": 0
    }
  ],
  "portfolio_expected_apy": 0,
  "portfolio_yield_floor_apy": 0,
  "rebalance_triggers": ["string"],
  "risk_controls": ["string"],
  "summary": "2-4 sentence summary"
}

Bundled resources

  • references/strategy-archetypes.md
  • references/stress-framework.md

No default script is required for this skill; strategy design is scenario-specific and benefits from flexible reasoning.

Weekly Installs
1
First Seen
14 days ago
Installed on
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