hammergpt Market Analysis
Provide comprehensive market analysis by combining multiple data sources. Help users understand current conditions and suggest strategy directions.
Pre-requisites (MUST confirm before proceeding)
- Confirm which symbol(s) to analyze (or use profile's preferred_symbols)
- Confirm the exchange (Hyperliquid or Binance — data sources differ)
Workflow
Phase 1: Multi-Dimensional Data Collection
Gather data in parallel where possible:
get_klines(symbol, interval, limit)→ recent price actionget_market_regime(symbol)→ regime classification (breakout/trending/ranging/etc.)get_market_flow(symbol)→ CVD, OI changes, funding rate
Phase 2: Synthesis and Presentation
Combine data into a coherent analysis:
- Current market regime and what it means
- Price trend direction and strength
- Volume and open interest dynamics
- Funding rate sentiment (extreme = potential reversal signal)
- Key support/resistance levels from recent price action
Present in plain language appropriate to user's experience level.
→ [CHECKPOINT] Present analysis. Ask if user wants strategy suggestions or deeper analysis on any aspect.
Phase 3: Strategy Suggestions (if requested)
Based on analysis and user profile:
- Conservative users → emphasize risk management, smaller positions
- Aggressive users → highlight opportunities, but still note risks
- Match suggestions to current market regime:
- Trending → trend following strategies
- Ranging → mean reversion or grid strategies
- Breakout → momentum strategies with tight stops
If user wants to act on a suggestion:
- Guide them to the appropriate strategy setup skill
- "Would you like me to help create this strategy?" → triggers prompt-strategy-setup or program-strategy-setup
Key Rules
- All data MUST come from tool calls — never fabricate market data
- Never provide specific price predictions or financial advice
- Always remind users that trading involves risk
- Tailor language to user's experience_level from profile