Pal MCP Toolkit
SkillMonitoring & opsComprehensive Pal MCP toolkit for code analysis, debugging, planning, refactoring, code review, and execution tracing. Provides systematic workflows with expert validation for complex development tasks.
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What this skill tells your AI
The instructions your AI receives, as published by pedronauck/skills in skills/community/pal/SKILL.md and read by ahel’s review.
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: falseis returned - ALWAYS increment
step_numberand call the tool again whennext_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
- Check
next_step_requiredin every response - If
true, call the tool again with incrementedstep_number - Never proceed with implementation while
next_step_required: true - 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 causeconfidence:"exploring"|"low"|"medium"|"high"|"very_high"|"almost_certain"|"certain"
See references/debug.md for complete documentation.
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 stepsis_branch_point: For exploring alternative approachesbranch_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 analysisseverity_filter:"all"to catch all severity levelsfocus_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
- Start: Call the tool with
step_number: 1and initial strategy - Iterate: Increment
step_numberand refine findings based on previous step - Continue: Keep calling until
next_step_required: false - 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
Signals
- GitHub stars
- 611
- Forks
- 88
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
pal- Source
- github.com/pedronauck/skills