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2025-11-30 08:58:42 +08:00

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description, category, complexity, mcp-servers, personas
description category complexity mcp-servers personas
Intelligent MCP tool selection based on complexity scoring and operation analysis special high
serena
morphllm

/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