/select-tool

/sc:select-tool - Intelligent MCP Tool Selection

Triggers

• Operations requiring optimal MCP tool selection between Serena and Morphllm
• Meta-system decisions needing complexity analysis and capability matching
• Tool routing decisions requiring performance vs accuracy trade-offs
• Operations benefiting from intelligent tool capability assessment

Usage

/sc:select-tool [operation] [--analyze] [--explain]

Behavioral Flow

1. Parse: Analyze operation type, scope, file count, and complexity indicators
2. Score: Apply multi-dimensional complexity scoring across various operation factors
3. Match: Compare operation requirements against Serena and Morphllm capabilities
4. Select: Choose optimal tool based on scoring matrix and performance requirements
5. Validate: Verify selection accuracy and provide confidence metrics

Key behaviors:

• Complexity scoring based on file count, operation type, language, and framework requirements
• Performance assessment evaluating speed vs accuracy trade-offs for optimal selection
• Decision logic matrix with direct mappings and threshold-based routing rules
• Tool capability matching for Serena (semantic operations) vs Morphllm (pattern operations)

MCP Integration

• Serena MCP: Optimal for semantic operations, LSP functionality, symbol navigation, and project context
• Morphllm MCP: Optimal for pattern-based edits, bulk transformations, and speed-critical operations
• Decision Matrix: Intelligent routing based on complexity scoring and operation characteristics

Tool Coordination

• get_current_config: System configuration analysis for tool capability assessment
• execute_sketched_edit: Operation testing and validation for selection accuracy
• Read/Grep: Operation context analysis and complexity factor identification
• Integration: Automatic selection logic used by refactor, edit, implement, and improve commands

Key Patterns

• Direct Mapping: Symbol operations → Serena, Pattern edits → Morphllm, Memory operations → Serena
• Complexity Thresholds: Score >0.6 → Serena, Score <0.4 → Morphllm, 0.4-0.6 → Feature-based
• Performance Trade-offs: Speed requirements → Morphllm, Accuracy requirements → Serena
• Fallback Strategy: Serena → Morphllm → Native tools degradation chain

Examples

Complex Refactoring Operation

/sc:select-tool "rename function across 10 files" --analyze
# Analysis: High complexity (multi-file, symbol operations)
# Selection: Serena MCP (LSP capabilities, semantic understanding)

Pattern-Based Bulk Edit

/sc:select-tool "update console.log to logger.info across project" --explain
# Analysis: Pattern-based transformation, speed priority
# Selection: Morphllm MCP (pattern matching, bulk operations)

Memory Management Operation

/sc:select-tool "save project context and discoveries"
# Direct mapping: Memory operations → Serena MCP
# Rationale: Project context and cross-session persistence

Boundaries

Will:

• Analyze operations and provide optimal tool selection between Serena and Morphllm
• Apply complexity scoring based on file count, operation type, and requirements
• Provide sub-100ms decision time with >95% selection accuracy

Will Not:

• Override explicit tool specifications when user has clear preference
• Select tools without proper complexity analysis and capability matching
• Compromise performance requirements for convenience or speed