Tool Selection

Tool Selection

Overview

Select the optimal MCP tool by evaluating task complexity, accuracy needs, and performance trade-offs.

When to Use

• Choosing between Codanna and Morphllm
• Routing tasks based on complexity
• Explaining tool selection rationale

Avoid when:

• The tool is explicitly specified by the user

Quick Reference

Workflow

1. Parse the operation requirements. 2. Load the tool selection reference. 3. Apply the scoring and decision matrix. 4. Report the chosen tool and rationale.

Output

• Selected tool and confidence
• Rationale and trade-offs

Common Mistakes

• Ignoring explicit user tool preferences
• Overweighting speed vs accuracy without justification

Reference: select

/tools:select - Intelligent MCP Tool Selection

Personas (Thinking Modes)

• architect: Complexity assessment, capability matching, operation analysis
• performance-engineer: Performance vs accuracy trade-offs, tool efficiency comparison
• tool-specialist: MCP tool capabilities, strength/weakness analysis, optimal routing

Delegation Protocol

This command does NOT delegate - Tool selection is direct analysis and decision.

Why no delegation:

• ❌ Fast complexity scoring (<5 seconds)
• ❌ Direct capability matching logic
• ❌ Simple scoring matrix application
• ❌ No external execution required (just decision)

All work done directly:

• Parse operation requirements
• Apply complexity scoring
• Match against Codanna and Morphllm capabilities
• Select optimal tool
• Provide confidence metrics

Note: This command uses MCP servers (Codanna, Morphllm) for understanding their capabilities, but doesn't delegate the selection logic itself. Personas guide the selection criteria.

Tool Coordination

• Codanna MCP: Capability query (direct API for metadata)
• Morphllm MCP: Capability query (direct API for metadata)
• Direct analysis: Complexity scoring and matching (direct logic)
• No delegation needed: Decision-making is direct

Triggers

• Operations requiring optimal MCP tool selection between Codanna 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

/tools:select [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 Codanna 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 Codanna (semantic operations) vs Morphllm (pattern operations)

MCP Integration

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

Examples

Complex Refactoring Operation

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

Pattern-Based Bulk Edit

/tools:select "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

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

Boundaries

Will:

• Analyze operations and provide optimal tool selection between Codanna 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