pal

name	pal
description	Comprehensive Pal MCP toolkit for code analysis, debugging, planning, refactoring, code review, and execution tracing. Provides systematic workflows with expert validation for complex development tasks.

Pal MCP Toolkit

The Pal MCP toolkit provides specialized tools for comprehensive code analysis and development workflows. Each tool follows a multi-step workflow pattern with expert validation.

Quick Reference: Tool Selection

Task Type	Tool	Reference
Architecture & code analysis before complex tasks	mcp__zen__analyze	analyze.md
Bug investigation & root cause analysis	mcp__zen__debug	debug.md
Strategic planning & task breakdown	mcp__zen__planner	planner.md
Code smell detection & refactoring	mcp__zen__refactor	refactor.md
Code review after completing tasks	mcp__zen__codereview	review.md
Execution flow & dependency tracing	mcp__zen__tracer	tracer.md

Critical Workflow Requirements

Mandatory Completion Rules

• NEVER stop a workflow before next_step_required: false is returned
• ALWAYS increment step_number and call the tool again when next_step_required: true
• TASK INVALIDATION: Incomplete workflows result in immediate task rejection
• NO EXCEPTIONS: Even if analysis seems complete after step 1, you MUST complete all steps

Model Requirement

• MANDATORY: Always use model: "anthropic/claude-opus-4.6" for ALL Pal MCP tool calls
• NEVER use any other model when calling Pal MCP tools

Workflow Validation Checklist

1. Check next_step_required in every response
2. If true, call the tool again with incremented step_number
3. Never proceed with implementation while next_step_required: true
4. Workflow is complete ONLY when next_step_required: false

Tool Overview

Analyze (mcp__zen__analyze)

When to Use:

• Before complex tasks to understand existing architecture
• Architecture review and system design assessment
• Performance, security, and technical debt analysis

Key Parameters:

• analysis_type: "architecture" | "performance" | "security" | "quality" | "general"
• output_format: "summary" | "detailed" | "actionable"

See references/analyze.md for complete documentation.

---

Debug (mcp__zen__debug)

When to Use:

• Bug investigation and root cause analysis
• Performance issues, memory leaks, race conditions
• Integration failures and service communication problems

Key Parameters:

• hypothesis: Current theory about the root cause
• confidence: "exploring" | "low" | "medium" | "high" | "very_high" | "almost_certain" | "certain"

See references/debug.md for complete documentation.

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Planner (mcp__zen__planner)

When to Use:

• Breaking down complex tasks into manageable steps
• System design and architectural decisions
• Migration planning and implementation strategies

Key Parameters:

• is_step_revision: For refining previous steps
• is_branch_point: For exploring alternative approaches
• branch_id: Naming alternative approaches

See references/planner.md for complete documentation.

---

Refactor (mcp__zen__refactor)

When to Use:

• Addressing code smells and technical debt
• Decomposing large modules or classes
• Modernizing legacy patterns

Key Parameters:

• refactor_type: "codesmells" | "decompose" | "modernize" | "organization"
• focus_areas: ["performance", "readability", "maintainability", "security"]

See references/refactor.md for complete documentation.

---

Code Review (mcp__zen__codereview)

When to Use:

• After completing a task (MANDATORY)
• Before submitting pull requests
• Validating implementation against project standards

Key Parameters:

• review_type: "full" for comprehensive analysis
• severity_filter: "all" to catch all severity levels
• focus_on: Specific areas like "performance", "security", "type-safety"

See references/review.md for complete documentation.

---

Tracer (mcp__zen__tracer)

When to Use:

• Understanding code execution paths
• Mapping dependencies before refactoring
• Debugging complex flows

Key Parameters:

• trace_mode: "precision" (execution flow) | "dependencies" (structural analysis) | "ask"
• target_description: Clear description of what to trace and why

See references/tracer.md for complete documentation.

Common Required Parameters

All Pal MCP tools require these base parameters:

{
  "step": "Description of current step",
  "step_number": 1,
  "total_steps": 2,
  "next_step_required": true,
  "findings": "Findings from this step",
  "model": "anthropic/claude-opus-4.6"
}

File Path Requirements

• ALWAYS use full absolute paths for relevant_files
• Include files directly involved in the analysis
• Include related files that provide context
• Include test files when relevant

Typical Workflow Pattern

1. Start: Call the tool with step_number: 1 and initial strategy
2. Iterate: Increment step_number and refine findings based on previous step
3. Continue: Keep calling until next_step_required: false
4. Complete: Only proceed with implementation after workflow completes

Violation Examples (Task Rejection)

• Calling a Pal tool once and proceeding to implementation
• Skipping steps because analysis seems complete
• Starting implementation before next_step_required: false
• Using a model other than anthropic/claude-opus-4.6