Ensures proper use of PAL MCP tools (thinkdeep, debug, codereview, consensus, planner) for complex tasks requiring deep analysis, multi-model collaboration, or systematic investigation. Auto-activates when: - User requests debugging, code review, or planning assistance - Complex problems require systematic investigation - Multi-model consensus needed for architectural decisions - Deep thinking required for root cause analysis Provides guidance on: - When to use each PAL MCP tool - Proper co...
Scanned 9/8/2026
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---
name: mcp-pal-usage
description: |
Ensures proper use of PAL MCP tools (thinkdeep, debug, codereview, consensus, planner)
for complex tasks requiring deep analysis, multi-model collaboration, or systematic
investigation.
Auto-activates when:
- User requests debugging, code review, or planning assistance
- Complex problems require systematic investigation
- Multi-model consensus needed for architectural decisions
- Deep thinking required for root cause analysis
Provides guidance on:
- When to use each PAL MCP tool
- Proper continuation_id management
- Model selection strategies
- Workflow orchestration patterns
allowed-tools: ["Read", "Grep", "mcp__pal__chat", "mcp__pal__thinkdeep", "mcp__pal__debug", "mcp__pal__codereview", "mcp__pal__consensus", "mcp__pal__planner", "mcp__pal__secaudit", "mcp__pal__precommit", "mcp__pal__listmodels", "mcp__pal__analyze", "mcp__pal__refactor", "mcp__pal__tracer", "mcp__pal__testgen", "mcp__pal__docgen", "mcp__pal__clink"]
---
# PAL MCP Usage Skill
This skill provides guidance on using PAL MCP tools effectively for complex software engineering tasks.
## Available PAL MCP Tools
### 1. `mcp__pal__chat` - General Collaboration
**Use for:**
- Brainstorming and ideation
- Getting second opinions
- Quick consultations
- Validation of approaches
**Example:**
```javascript
mcp__pal__chat({
model: "haiku", // Fast for simple tasks
prompt: "Review this approach for implementing dark mode",
absolute_file_paths: ["/path/to/ThemeManager.swift"],
working_directory_absolute_path: "/path/to/project"
})
```
**When NOT to use:**
- Systematic debugging → use `debug` instead
- Code review → use `codereview` instead
- Strategic planning → use `planner` instead
---
### 2. `mcp__pal__debug` - Systematic Debugging
**Use for:**
- Complex bugs with unclear root cause
- Race conditions and concurrency issues
- Memory leaks and performance problems
- Mysterious crashes
**Example:**
```javascript
mcp__pal__debug({
model: "gemini-2.5-pro", // Deep analysis capability
step: "Investigate SwiftData relationship crash in LibraryView",
step_number: 1,
total_steps: 3,
next_step_required: true,
findings: "App crashes when accessing book.author.name. Suspect SwiftData fault issue.",
hypothesis: "Accessing unfaulted relationship on background thread",
relevant_files: ["/path/to/LibraryView.swift", "/path/to/Work.swift"],
files_checked: ["/path/to/LibraryView.swift"],
confidence: "medium"
})
```
**Confidence levels:**
- `exploring` - Just starting investigation
- `low` - Early hypothesis
- `medium` - Some evidence gathered
- `high` - Strong evidence
- `very_high` - Very confident
- `almost_certain` - Nearly proven
- `certain` - 100% confirmed locally (skips external validation)
**Critical:** Always reuse `continuation_id` for multi-step debugging!
---
### 3. `mcp__pal__codereview` - Systematic Code Review
**Use for:**
- Comprehensive quality assessment
- Security vulnerability scanning
- Architecture validation
- Performance analysis
**Review types:**
- `full` - Complete review (quality, security, performance, architecture)
- `security` - Security-focused audit
- `performance` - Performance bottleneck analysis
- `quick` - Fast high-level review
**Example:**
```javascript
mcp__pal__codereview({
model: "grok-code-fast-1", // Expert review capability
step: "Review EnrichmentService for security and performance",
step_number: 1,
total_steps: 2,
next_step_required: true,
findings: "Starting comprehensive review...",
relevant_files: ["/path/to/EnrichmentService.swift"],
review_type: "full",
confidence: "medium"
})
```
**Validation types:**
- `external` (default) - Expert model validation after your review
- `internal` - Local-only review (faster, less thorough)
---
### 4. `mcp__pal__secaudit` - Security Audit
**Use for:**
- OWASP Top 10 vulnerability scanning
- Security compliance validation
- Pre-deployment security checks
- Sensitive code path review
**Audit focus:**
- `owasp` - OWASP Top 10 vulnerabilities
- `compliance` - Regulatory compliance (GDPR, SOC2, etc.)
- `infrastructure` - Infrastructure security (API keys, secrets)
- `dependencies` - Third-party dependency vulnerabilities
- `comprehensive` - All of the above
**Example:**
```javascript
mcp__pal__secaudit({
model: "grok-code-fast-1", // Security expertise
step: "Audit AuthenticationService for OWASP vulnerabilities",
step_number: 1,
total_steps: 2,
next_step_required: true,
findings: "Analyzing API key handling and session management...",
relevant_files: ["/path/to/AuthenticationService.swift"],
audit_focus: "owasp",
threat_level: "high",
confidence: "medium"
})
```
**Threat levels:**
- `low` - Internal tools, non-production
- `medium` - Production app with limited exposure
- `high` - Public-facing production service
- `critical` - Handles sensitive PII or financial data
---
### 5. `mcp__pal__planner` - Interactive Planning
**Use for:**
- Complex project planning
- Multi-phase migrations
- Architectural design sessions
- Strategic refactoring plans
**Features:**
- Step-by-step planning with revision capability
- Branch exploration for alternative approaches
- Expert model validation of plans
**Example:**
```javascript
mcp__pal__planner({
model: "gemini-2.5-pro", // Strategic thinking
step: "Plan migration from KV storage to D1 database",
step_number: 1,
total_steps: 5,
next_step_required: true
})
// Later: Branch to explore alternative approach
mcp__pal__planner({
continuation_id: "abc123", // REUSE ID!
model: "gemini-2.5-pro",
step: "Explore zero-downtime migration using dual-write pattern",
step_number: 3,
total_steps: 5,
next_step_required: true,
is_branch_point: true,
branch_id: "zero-downtime-approach",
branch_from_step: 2
})
```
---
### 6. `mcp__pal__consensus` - Multi-Model Consensus
**Use for:**
- Critical architectural decisions
- Technology selection
- Complex trade-off analysis
- Design pattern selection
**Example:**
```javascript
mcp__pal__consensus({
step: "Evaluate: Should we use SwiftData or Core Data for BooksTrack v4?",
step_number: 1,
total_steps: 4, // 3 models + synthesis
next_step_required: true,
findings: "Initial analysis: SwiftData offers modern API, Core Data more mature",
models: [
{model: "gemini-2.5-pro", stance: "for"}, // Pro-SwiftData
{model: "grok-code-fast-1", stance: "against"}, // Pro-Core Data
{model: "claude-opus-4", stance: "neutral"} // Unbiased analysis
],
relevant_files: ["/path/to/Work.swift", "/path/to/Author.swift"]
})
```
**Stances:**
- `for` - Argue in favor of proposal
- `against` - Argue against proposal
- `neutral` - Unbiased analysis
---
### 7. `mcp__pal__precommit` - Pre-Commit Validation
**Use for:**
- Validating git changes before commit
- Multi-repository change validation
- Impact assessment
- Completeness verification
**Example:**
```javascript
mcp__pal__precommit({
model: "grok-code-fast-1",
step: "Validate staged changes for completeness and security",
path: "/path/to/repo",
step_number: 1,
total_steps: 3,
next_step_required: true,
findings: "Analyzing git diff and impact...",
include_staged: true,
include_unstaged: true,
confidence: "medium"
})
```
**Validation options:**
- Compare to specific branch: `compare_to: "main"`
- Focus on specific concerns: `focus_on: "security"`
- Filter by severity: `severity_filter: "high"`
---
### 8. `mcp__pal__thinkdeep` - Deep Thinking
**Use for:**
- Complex problem analysis
- Architecture decisions requiring deep reasoning
- Performance challenges
- Multi-stage investigation
**Similar to `debug` but more general-purpose.**
**Example:**
```javascript
mcp__pal__thinkdeep({
model: "gemini-2.5-pro",
step: "Analyze the architectural implications of real-time sync",
step_number: 1,
total_steps: 3,
next_step_required: true,
findings: "Exploring WebSocket vs SSE vs polling trade-offs...",
hypothesis: "SSE provides best balance of simplicity and reliability",
focus_areas: ["architecture", "performance", "reliability"],
confidence: "medium"
})
```
---
## Model Selection Guide
**Use `listmodels` to see all available models:**
```javascript
mcp__pal__listmodels()
```
**Top Models (as of v2.0.60):**
- **grok-code-fast-1** (256K context, code specialist, 70.8% SWE-Bench)
- Best for: Code review, security audits, architecture validation
- Score: 100
- **gemini-2.5-pro** (1M context, thinking mode, code generation)
- Best for: Deep analysis, debugging, strategic planning
- Score: 100
- **gemini-3-pro-preview** (1M context, thinking mode, latest)
- Best for: Cutting-edge analysis, complex reasoning
- Score: 100
- **grok-4-1-fast-non-reasoning** (2M context)
- Best for: Large codebase analysis, massive context requirements
- Score: 100
- **haiku** (fast, efficient)
- Best for: Quick consultations, simple implementations
- Auto-uses Sonnet in plan mode
---
## Critical Continuation Pattern
**ALWAYS reuse `continuation_id` for multi-turn conversations:**
```javascript
// First call
const step1 = await mcp__pal__debug({
model: "gemini-2.5-pro",
step: "Investigate crash",
// ...
});
// Returns: continuation_id: "xyz789"
// Follow-up (CRITICAL: REUSE ID!)
const step2 = await mcp__pal__debug({
continuation_id: "xyz789", // ← MUST REUSE!
model: "gemini-2.5-pro",
step: "Continue investigation with new findings",
// ...
});
```
**Why this matters:**
- Preserves full conversation context
- Maintains investigation state
- Enables seamless resumption
- Prevents redundant work
---
## Workflow Decision Tree
```
User request
├─ "Debug this crash/bug/issue"
│ → Use mcp__pal__debug
│
├─ "Review this code"
│ → Use mcp__pal__codereview
│
├─ "Audit for security issues"
│ → Use mcp__pal__secaudit
│
├─ "Plan this migration/feature"
│ → Use mcp__pal__planner
│
├─ "Should we use X or Y?"
│ → Use mcp__pal__consensus
│
├─ "Validate my changes before commit"
│ → Use mcp__pal__precommit
│
├─ "Analyze this complex problem"
│ → Use mcp__pal__thinkdeep
│
└─ "Quick question about approach"
→ Use mcp__pal__chat
```
---
## Integration with Claude Code Agents
**This skill works alongside:**
- **cloudflare-specialist** - Cloudflare-specific architecture
- **code-review-grok** - Wraps `mcp__pal__codereview` with project context
- **security-auditor** - Wraps `mcp__pal__secaudit` with project context
- **performance-analyzer** - Wraps `mcp__pal__thinkdeep` for performance
**Skill activates proactively to ensure:**
- Correct tool selection
- Proper continuation_id management
- Appropriate model selection
- Complete workflow execution
---
## Common Anti-Patterns
### ❌ Don't: Forget continuation_id
```javascript
// First call - gets continuation_id
mcp__pal__debug({ step: "Step 1", ... });
// Second call - WRONG! No continuation_id
mcp__pal__debug({ step: "Step 2", ... });
```
### ✅ Do: Always reuse continuation_id
```javascript
// First call
const result1 = mcp__pal__debug({ step: "Step 1", ... });
const contId = result1.continuation_id;
// Second call - CORRECT!
mcp__pal__debug({ continuation_id: contId, step: "Step 2", ... });
```
---
### ❌ Don't: Use wrong tool for task
```javascript
// Debugging a crash with chat tool (too shallow)
mcp__pal__chat({ prompt: "Why does this crash?" });
```
### ✅ Do: Use systematic debugging tool
```javascript
// Proper systematic investigation
mcp__pal__debug({
step: "Investigate crash in LibraryView",
hypothesis: "SwiftData concurrency issue",
// ...
});
```
---
### ❌ Don't: Skip model selection
```javascript
// No model specified - uses default
mcp__pal__codereview({ step: "Review code", ... });
```
### ✅ Do: Choose appropriate model
```javascript
// Explicit model selection for security expertise
mcp__pal__codereview({
model: "grok-code-fast-1", // Security specialist
step: "Review for OWASP vulnerabilities",
// ...
});
```
---
## Quick Reference Card
| Task | Tool | Model | Why |
|------|------|-------|-----|
| Debug crash | `debug` | gemini-2.5-pro | Deep analysis, 1M context |
| Review code | `codereview` | grok-code-fast-1 | Code specialist, security focus |
| Security audit | `secaudit` | grok-code-fast-1 | OWASP expertise |
| Plan migration | `planner` | gemini-2.5-pro | Strategic thinking |
| Tech decision | `consensus` | 3+ models | Multiple perspectives |
| Validate commit | `precommit` | grok-code-fast-1 | Quality assurance |
| Analyze problem | `thinkdeep` | gemini-2.5-pro | Deep reasoning |
| Quick question | `chat` | haiku | Fast, efficient |
---
## Async PAL MCP Usage (v2.0.64)
**Long-running PAL analyses can run in background:**
```javascript
// Launch comprehensive debug session in background
Task({
subagent_type: "pal",
prompt: "Deep investigation of memory leak in LibraryView",
run_in_background: true
})
// Continue with other work...
// Retrieve results when ready
TaskOutput({
task_id: "agent_xyz123",
block: true,
timeout: 180000 // 3 minutes for deep analysis
})
```
**Background-friendly operations:**
- `mcp__pal__debug` - Complex multi-step debugging
- `mcp__pal__codereview` with `review_type: "full"`
- `mcp__pal__secaudit` with `audit_focus: "comprehensive"`
- `mcp__pal__consensus` - Multi-model deliberation
**Keep synchronous:**
- `mcp__pal__chat` - Quick consultations
- `mcp__pal__codereview` with `review_type: "quick"`
- `mcp__pal__challenge` - Immediate critical thinking
---
## Named Sessions (v2.0.64)
For long debugging/review sessions, name your session:
```
/rename debug-memory-leak
```
Resume later from terminal:
```bash
claude --resume debug-memory-leak
```
---
## Recommended Options (v2.0.62)
When presenting choices, add "(Recommended)" to preferred option:
```javascript
AskUserQuestion({
questions: [{
question: "Which analysis depth?",
header: "Analysis",
options: [
{label: "Quick review (Recommended)", description: "Fast, single-file"},
{label: "Full analysis", description: "Comprehensive, multi-file"},
{label: "Deep investigation", description: "Maximum depth, longest time"}
]
}]
})
```
---
**Last Updated:** December 11, 2025 (v2.0.65)
**Maintained by:** BooksTrack Project
**Related Skills:** cloudflare-api-orchestration
**Related Agents:** code-review-grok, security-auditor, performance-analyzer
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