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Adolf is a fork/vendored clone of github.com/openclaw/openclaw (v2026.6.11), free to diverge. Tree copied sans upstream .git; upstream remote added for future syncs. Node pinned to 24 (.nvmrc); engines already require >=22.19. Preserves docs/ARCHITECTURE.md. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LeqyaxJF2nbRXJtae2kNB2
87 lines
2.9 KiB
Plaintext
87 lines
2.9 KiB
Plaintext
# Choice Blocks Example
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# Demonstrates AI-selected branching based on runtime criteria
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# Simple choice based on analysis
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let analysis = session "Analyze the current codebase quality"
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choice **the severity of issues found**:
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option "Critical":
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session "Stop all work and fix critical issues immediately"
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context: analysis
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session "Create incident report"
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option "Moderate":
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session "Schedule fixes for next sprint"
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context: analysis
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option "Minor":
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session "Add to technical debt backlog"
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context: analysis
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# Choice for user experience level
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choice **the user's technical expertise based on their question**:
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option "Beginner":
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session "Explain concepts from first principles"
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session "Provide step-by-step tutorial"
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session "Include helpful analogies"
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option "Intermediate":
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session "Give concise explanation with examples"
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session "Link to relevant documentation"
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option "Expert":
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session "Provide technical deep-dive"
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session "Include advanced configuration options"
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# Choice for project approach
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let requirements = session "Gather project requirements"
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choice **the best development approach given the requirements**:
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option "Rapid prototype":
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session "Create quick MVP focusing on core features"
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context: requirements
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session "Plan iteration cycle"
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option "Production-ready":
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session "Design complete architecture"
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context: requirements
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session "Set up CI/CD pipeline"
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session "Implement with full test coverage"
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option "Research spike":
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session "Explore technical feasibility"
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context: requirements
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session "Document findings and recommendations"
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# Multi-line criteria for complex decisions
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let market_data = session "Gather market research data"
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let tech_analysis = session "Analyze technical landscape"
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choice ***
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the optimal market entry strategy
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considering both market conditions
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and technical readiness
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***:
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option "Aggressive launch":
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session "Prepare for immediate market entry"
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context: [market_data, tech_analysis]
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option "Soft launch":
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session "Plan limited beta release"
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context: [market_data, tech_analysis]
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option "Wait and iterate":
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session "Continue development and monitor market"
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context: [market_data, tech_analysis]
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# Nested choices for detailed decision trees
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let request = session "Analyze incoming customer request"
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choice **the type of request**:
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option "Technical support":
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choice **the complexity of the technical issue**:
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option "Simple":
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session "Provide self-service solution"
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context: request
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option "Complex":
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session "Escalate to senior engineer"
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context: request
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option "Sales inquiry":
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session "Forward to sales team with context"
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context: request
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option "Feature request":
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session "Add to product backlog and notify PM"
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context: request
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