deep-analysis
Uses multiple parallel finder agents and multiple oracle consultations simultaneously for broad analysis. Use when asked to search from multiple angles, investigate across many files, or need parallel multi-perspective analysis.
When & Why to Use This Skill
This Claude skill facilitates thorough codebase investigations through parallel agent orchestration and multi-perspective analysis. It streamlines complex debugging, architectural reviews, and system-wide assessments by synthesizing insights from multiple specialized search and oracle agents, making it an essential tool for understanding large-scale software projects.
Use Cases
- Complex Debugging: Rapidly identifying root causes of system-wide issues by searching across multiple files and modules in parallel to find hidden dependencies.
- Architectural Analysis: Evaluating design patterns and structural integrity to ensure the codebase meets scalability and maintainability standards.
- Cross-Cutting Concerns: Investigating the implementation of global features like security, performance, or logging across the entire repository to ensure consistency.
- Deep Code Audits: Conducting comprehensive reviews of legacy code or large-scale changes using multiple expert perspectives for maximum quality assurance.
| name | deep-analysis |
|---|---|
| description | Uses multiple parallel finder agents and multiple oracle consultations simultaneously for broad analysis. Use when asked to search from multiple angles, investigate across many files, or need parallel multi-perspective analysis. |
Deep Analysis
Performs thorough codebase investigation using parallel search agents and multiple oracle consultations for comprehensive analysis.
When to Use
- Complex debugging across multiple files
- Architecture or design pattern analysis
- Understanding cross-cutting concerns
- Investigating system-wide issues
- Deep code review and quality assessment
Workflow
Phase 1: Parallel Search
Launch multiple finder agents simultaneously to explore different aspects:
1. Search for core functionality: finder("Find the main implementation of [feature]")
2. Search for related components: finder("Find all components that interact with [feature]")
3. Search for tests: finder("Find all tests related to [feature]")
4. Search for configuration: finder("Find configuration and settings for [feature]")
Execute all finder calls in parallel for maximum efficiency.
Phase 2: Multi-Oracle Analysis
After gathering search results, consult the oracle multiple times for different perspectives:
1. Oracle #1 - Architecture Review:
oracle(task: "Review the architecture of [feature]", files: [relevant_files])
2. Oracle #2 - Code Quality Analysis:
oracle(task: "Analyze code quality, patterns, and potential issues", files: [relevant_files])
3. Oracle #3 - Integration Analysis:
oracle(task: "Analyze how components integrate and identify coupling issues", files: [relevant_files])
Phase 3: Synthesis
Combine insights from all oracles to provide:
- Comprehensive understanding of the system
- Identified issues and their root causes
- Actionable recommendations
- Priority ranking of findings
Best Practices
- Parallel Execution: Always run independent finder calls in a single message block
- Focused Queries: Each finder/oracle should have a specific, focused objective
- Progressive Depth: Start broad, then drill down into problem areas
- Cross-Reference: Use oracle findings to guide additional targeted searches
- Document Findings: Use todo_write to track discoveries and action items
Example Usage
For investigating a performance issue:
Phase 1 - Parallel Search:
- finder("Find database query implementations")
- finder("Find caching mechanisms")
- finder("Find API endpoint handlers")
- finder("Find performance-related tests or benchmarks")
Phase 2 - Oracle Analysis:
- oracle: "Analyze database query patterns for N+1 issues"
- oracle: "Review caching strategy effectiveness"
- oracle: "Identify bottlenecks in request handling"
Phase 3 - Synthesize and Report