Score contract, liquidity, concentration, social, and narrative risks before trade proposals.
npx skills add https://github.com/0xb11a/crypto-claw --skill risk-0xb11a
Please help me install this Agent Skill. Skill: risk Source: https://github.com/0xb11a/crypto-claw/tree/main/agents/research/skills/risk Command: npx skills add https://github.com/0xb11a/crypto-claw --skill risk-0xb11a
Pre-trade risk assessment is essential to prevent costly mistakes in automated trading. This skill provides automated scoring and safety checks before any trade proposal.
Trigger the risk check during the heartbeat, pass all gathered data, and read the resulting JSON verdict to decide approval, caution, or rejection.
High-intent search queries and answers about installing and using this skill.
Pre-trade risk assessment automates contract, liquidity, concentration, social, and narrative scoring to filter unsafe crypto trade proposals. It runs during heartbeat cycles and outputs a JSON verdict of approval, caution, or rejection.
Crypto trading risk checks evaluate contract vulnerabilities, liquidity depth, concentration levels, social signals, and narrative scoring. Market regime modifiers apply to these scores to auto-reject dangerous opportunities.
Auto-reject logic activates by triggering risk checks during heartbeat cycles. The system applies market regime modifiers to risk scores and outputs a JSON verdict that automatically blocks dangerous trading signals.
Portfolio risk checking during heartbeat cycles vets and gates trade proposals by passing gathered data through scoring. The resulting JSON verdict determines if the portfolio update is approved, cautioned, or rejected.
Risk scoring filters unsafe opportunities across market regimes by applying regime modifiers to token and portfolio checks. This ensures unsafe signals are auto-rejected during unfavorable market conditions.
Automated crypto trade safety checks should not replace manual review for novel contract architectures or low-liquidity assets where scoring models may lack sufficient data to generate accurate risk verdicts.
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