sc-analyze
π―Skillfrom tony363/superclaude
Performs comprehensive code analysis across quality, security, performance, and architecture domains, generating actionable insights and recommendations.
Installation
npx skills add https://github.com/tony363/superclaude --skill sc-analyzeSkill Details
Comprehensive code analysis, quality assessment, and issue diagnosis. Use when analyzing code quality, security vulnerabilities, performance bottlenecks, architecture reviews, or troubleshooting bugs and build failures.
Overview
# Analysis & Troubleshooting Skill
Multi-domain code analysis with issue diagnosis and resolution capabilities.
Quick Start
```bash
# Quality analysis
/sc:analyze [target] --focus quality|security|performance|architecture
# Troubleshooting mode
/sc:analyze [issue] --troubleshoot --focus bug|build|performance|deployment
# With auto-fix
/sc:analyze "TypeScript errors" --troubleshoot --focus build --fix
```
Behavioral Flow
- Discover - Categorize source files, detect languages
- Scan - Apply domain-specific analysis techniques
- Evaluate - Generate prioritized findings with severity
- Recommend - Create actionable recommendations
- Report - Present comprehensive analysis with metrics
Flags
| Flag | Type | Default | Description |
|------|------|---------|-------------|
| --focus | string | quality | quality, security, performance, architecture, bug, build, deployment |
| --troubleshoot | bool | false | Enable issue diagnosis mode |
| --trace | bool | false | Detailed trace analysis for debugging |
| --fix | bool | false | Auto-apply safe fixes |
| --depth | string | standard | quick, standard, deep |
| --format | string | text | text, json, report |
Analysis Domains
Quality Analysis
- Code smells and maintainability issues
- Pattern violations and anti-patterns
- Technical debt assessment
Security Analysis
- Vulnerability scanning
- Compliance validation
- Authentication/authorization review
Performance Analysis
- Bottleneck identification
- Resource utilization patterns
- Optimization opportunities
Architecture Analysis
- Component coupling assessment
- Dependency analysis
- Design pattern evaluation
Troubleshooting Mode
When --troubleshoot is enabled:
| Focus | Behavior |
|-------|----------|
| bug | Error analysis, stack traces, code inspection |
| build | Build logs, dependencies, config validation |
| performance | Metrics analysis, bottleneck identification |
| deployment | Environment analysis, service validation |
Examples
Security Deep Dive
```
/sc:analyze src/auth --focus security --depth deep
```
Build Failure Fix
```
/sc:analyze "compilation errors" --troubleshoot --focus build --fix
```
Performance Diagnosis
```
/sc:analyze "slow API response" --troubleshoot --focus performance --trace
```
MCP Integration
PAL MCP (Always Use)
| Tool | When to Use | Purpose |
|------|-------------|---------|
| mcp__pal__thinkdeep | Complex issues | Multi-stage investigation with hypothesis testing |
| mcp__pal__debug | Bug troubleshooting | Systematic root cause analysis |
| mcp__pal__codereview | Quality analysis | Comprehensive code quality, security, performance review |
| mcp__pal__consensus | Critical findings | Multi-model validation of security/architecture issues |
| mcp__pal__challenge | Uncertain findings | Force critical thinking on ambiguous issues |
| mcp__pal__apilookup | Dependency issues | Get current API docs for version conflicts |
PAL Usage Patterns
```bash
# Deep investigation (--depth deep)
mcp__pal__thinkdeep(
step="Investigating performance bottleneck in API layer",
hypothesis="Database queries lack proper indexing",
confidence="medium",
relevant_files=["/src/api/users.py"]
)
# Security analysis (--focus security)
mcp__pal__codereview(
review_type="security",
findings="Authentication, authorization, injection vectors",
issues_found=[{"severity": "high", "description": "SQL injection risk"}]
)
# Critical finding validation
mcp__pal__consensus(
models=[
{"model": "gpt-5.2", "stance": "for"},
{"model": "gemini-3-pro", "stance": "against"}
],
step="Evaluate: Is this a critical security vulnerability?"
)
```
Rube MCP (When Needed)
| Tool | When to Use | Purpose |
|------|-------------|---------|
| mcp__rube__RUBE_SEARCH_TOOLS | External analysis | Find security scanners, linters |
| mcp__rube__RUBE_MULTI_EXECUTE_TOOL | Issue tracking | Create tickets for findings |
| mcp__rube__RUBE_REMOTE_WORKBENCH | Bulk analysis | Process large codebases |
Rube Usage Patterns
```bash
# Find and create Jira tickets for findings
mcp__rube__RUBE_SEARCH_TOOLS(queries=[
{"use_case": "create jira issue", "known_fields": "project:SECURITY"}
])
# Notify team of critical findings
mcp__rube__RUBE_MULTI_EXECUTE_TOOL(tools=[
{"tool_slug": "SLACK_SEND_MESSAGE", "arguments": {"channel": "#security", "text": "Critical finding..."}}
])
```
Flags (Extended)
| Flag | Type | Default | Description |
|------|------|---------|-------------|
| --pal-deep | bool | false | Use PAL thinkdeep for multi-stage analysis |
| --pal-review | bool | false | Use PAL codereview for comprehensive review |
| --consensus | bool | false | Use PAL consensus for critical findings |
| --notify | string | - | Notify via Rube (slack, jira, email) |
| --create-tickets | bool | false | Create tickets for findings via Rube |
Tool Coordination
- Glob - File discovery and structure analysis
- Grep - Pattern analysis and code search
- Read - Source inspection and config analysis
- Bash - External tool execution
- Write - Report generation
- PAL MCP - Multi-model analysis, debugging, code review
- Rube MCP - External notifications, ticket creation
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