Deep Analysis Skill
Comprehensive analytical templates for thorough investigation, audits, and evaluations leveraging extended thinking capabilities.
When to Use
- Code audits requiring systematic review
- Security assessments and threat modeling
- Performance analysis and optimization planning
- Architecture reviews and technical debt assessment
- Incident post-mortems and root cause analysis
- Compliance audits and risk assessments
Analysis Templates
Code Audit Template
markdown## Code Audit Report **Repository**: [repo-name] **Scope**: [files/modules audited] **Date**: [YYYY-MM-DD] **Auditor**: Claude + [Human reviewer] ### Executive Summary [2-3 sentence overview of findings] ### Audit Criteria - [ ] Code quality and maintainability - [ ] Security vulnerabilities - [ ] Performance concerns - [ ] Test coverage - [ ] Documentation completeness - [ ] Dependency health ### Critical Findings | ID | Severity | Location | Issue | Recommendation | |----|----------|----------|-------|----------------| | C1 | Critical | file:line | [Issue] | [Fix] | | C2 | Critical | file:line | [Issue] | [Fix] | ### High Priority Findings | ID | Severity | Location | Issue | Recommendation | |----|----------|----------|-------|----------------| | H1 | High | file:line | [Issue] | [Fix] | ### Medium Priority Findings [...] ### Low Priority / Suggestions [...] ### Metrics | Metric | Value | Target | Status | |--------|-------|--------|--------| | Test Coverage | 75% | 80% | ⚠️ | | Cyclomatic Complexity | 12 | <10 | ⚠️ | | Technical Debt | 4.2d | <3d | ❌ | | Security Score | 8/10 | 9/10 | ⚠️ | ### Recommendations 1. **Immediate**: [Critical fixes] 2. **Short-term**: [Within sprint] 3. **Long-term**: [Tech debt reduction] ### Sign-off - [ ] All critical issues addressed - [ ] High priority issues have timeline - [ ] Audit findings documented in backlog
Security Threat Model Template
markdown## Threat Model: [System/Component Name] **Version**: [1.0] **Last Updated**: [YYYY-MM-DD] **Classification**: [Internal/Confidential] ### System Overview [Brief description of the system being modeled] ### Assets | Asset | Description | Sensitivity | Owner | |-------|-------------|-------------|-------| | User Data | PII, credentials | Critical | Auth Team | | API Keys | Service credentials | High | DevOps | | Business Data | Transactions | High | Product | ### Trust Boundaries
┌─────────────────────────────────────────┐ │ External (Untrusted) │ │ [Internet Users] [Third-party APIs] │ └──────────────────┬──────────────────────┘ │ WAF/Load Balancer ┌──────────────────┴──────────────────────┐ │ DMZ (Semi-trusted) │ │ [API Gateway] [CDN] [Public Services] │ └──────────────────┬──────────────────────┘ │ Internal Firewall ┌──────────────────┴──────────────────────┐ │ Internal (Trusted) │ │ [App Servers] [Databases] [Queues] │ └─────────────────────────────────────────┘
### Threat Categories (STRIDE) #### Spoofing | Threat | Likelihood | Impact | Mitigation | |--------|------------|--------|------------| | Credential theft | Medium | High | MFA, rate limiting | | Session hijacking | Low | High | Secure cookies, HTTPS | #### Tampering | Threat | Likelihood | Impact | Mitigation | |--------|------------|--------|------------| | SQL injection | Medium | Critical | Parameterized queries | | Data modification | Low | High | Integrity checks | #### Repudiation [...] #### Information Disclosure [...] #### Denial of Service [...] #### Elevation of Privilege [...] ### Attack Vectors 1. **Vector 1**: [Description] - Entry point: [Where] - Technique: [How] - Mitigation: [Defense] ### Risk Matrix | Threat | Likelihood | Impact | Risk Score | Priority | |--------|------------|--------|------------|----------| | T1 | High | Critical | 9 | P1 | | T2 | Medium | High | 6 | P2 | | T3 | Low | Medium | 3 | P3 | ### Security Controls | Control | Type | Status | Coverage | |---------|------|--------|----------| | WAF | Preventive | ✅ Active | External | | SAST | Detective | ✅ CI/CD | Code | | DAST | Detective | ⚠️ Partial | Runtime | | Encryption | Preventive | ✅ Active | Data | ### Recommendations 1. [Priority 1 recommendations] 2. [Priority 2 recommendations] 3. [Priority 3 recommendations]
Performance Analysis Template
markdown## Performance Analysis Report **System**: [System name] **Period**: [Date range] **Environment**: [Production/Staging] ### Executive Summary [Key findings and recommendations] ### Performance Metrics #### Response Times | Endpoint | P50 | P95 | P99 | Target | Status | |----------|-----|-----|-----|--------|--------| | /api/users | 45ms | 120ms | 350ms | <200ms | ✅ | | /api/search | 230ms | 890ms | 2.1s | <500ms | ❌ | | /api/reports | 1.2s | 3.4s | 8.2s | <2s | ❌ | #### Throughput | Service | Current RPS | Peak RPS | Capacity | Utilization | |---------|-------------|----------|----------|-------------| | API | 1,200 | 2,400 | 5,000 | 48% | | Worker | 500 | 800 | 1,000 | 80% | #### Resource Utilization | Resource | Average | Peak | Threshold | Status | |----------|---------|------|-----------|--------| | CPU | 45% | 78% | 80% | ⚠️ | | Memory | 62% | 85% | 85% | ⚠️ | | Disk I/O | 30% | 55% | 70% | ✅ | | Network | 25% | 40% | 60% | ✅ | ### Bottleneck Analysis #### Identified Bottlenecks 1. **Database Queries** (High Impact) - Location: `/api/search` endpoint - Cause: Missing index on `created_at` column - Impact: 890ms P95 latency - Fix: Add composite index 2. **Memory Pressure** (Medium Impact) - Location: Report generation service - Cause: Large dataset loading into memory - Impact: GC pauses, OOM risks - Fix: Implement streaming/pagination ### Load Test Results | Scenario | Users | Duration | Errors | Avg Response | |----------|-------|----------|--------|--------------| | Baseline | 100 | 10min | 0% | 120ms | | Normal | 500 | 30min | 0.1% | 180ms | | Peak | 1000 | 15min | 2.3% | 450ms | | Stress | 2000 | 5min | 15% | 2.1s | ### Optimization Recommendations #### Quick Wins (This Sprint) 1. Add database indexes - Expected: 40% improvement 2. Enable query caching - Expected: 25% improvement 3. Optimize N+1 queries - Expected: 30% improvement #### Medium Term (Next Quarter) 1. Implement read replicas 2. Add CDN for static assets 3. Optimize serialization #### Long Term (6+ Months) 1. Service decomposition 2. Event-driven architecture 3. Edge computing deployment ### Capacity Planning | Timeframe | Expected Load | Current Capacity | Gap | Action | |-----------|---------------|------------------|-----|--------| | 3 months | +25% | 5,000 RPS | ✅ | Monitor | | 6 months | +50% | 5,000 RPS | ⚠️ | Scale | | 12 months | +100% | 5,000 RPS | ❌ | Redesign |
Architecture Review Template
markdown## Architecture Review **System**: [System name] **Version**: [Current architecture version] **Review Date**: [YYYY-MM-DD] **Participants**: [Team members] ### Current Architecture #### System Diagram
[Include architecture diagram or ASCII representation]
#### Components | Component | Purpose | Technology | Owner | |-----------|---------|------------|-------| | API Gateway | Request routing | Kong | Platform | | Auth Service | Authentication | Keycloak | Security | | Core API | Business logic | Python/FastAPI | Backend | | Database | Data persistence | PostgreSQL | Data | #### Data Flow 1. User request → API Gateway 2. API Gateway → Auth validation 3. Auth → Core API 4. Core API → Database 5. Response → User ### Evaluation Criteria #### Scalability | Aspect | Current | Target | Gap | Score | |--------|---------|--------|-----|-------| | Horizontal scaling | Manual | Auto | Yes | 6/10 | | Database scaling | Single | Sharded | Yes | 5/10 | | Caching | Redis | Distributed | No | 8/10 | #### Reliability | Aspect | Current | Target | Gap | Score | |--------|---------|--------|-----|-------| | Availability | 99.5% | 99.9% | Yes | 7/10 | | Disaster recovery | Manual | Auto | Yes | 5/10 | | Data backup | Daily | Real-time | Yes | 6/10 | #### Maintainability | Aspect | Current | Target | Gap | Score | |--------|---------|--------|-----|-------| | Code modularity | Medium | High | Yes | 6/10 | | Documentation | Partial | Complete | Yes | 5/10 | | Test coverage | 70% | 85% | Yes | 7/10 | ### Technical Debt Assessment | Item | Impact | Effort | Priority | Age | |------|--------|--------|----------|-----| | Legacy auth system | High | High | P1 | 2y | | Monolithic API | Medium | High | P2 | 1.5y | | Missing monitoring | Medium | Low | P1 | 1y | ### Recommendations #### Immediate (0-3 months) 1. [Recommendation 1] 2. [Recommendation 2] #### Short-term (3-6 months) 1. [Recommendation 1] 2. [Recommendation 2] #### Long-term (6-12 months) 1. [Recommendation 1] 2. [Recommendation 2] ### Decision Log | Decision | Rationale | Alternatives Considered | Date | |----------|-----------|------------------------|------| | [Decision 1] | [Why] | [Options] | [Date] |
Integration with Extended Thinking
For deep analysis tasks, use maximum thinking budget:
pythonresponse = client.messages.create( model="claude-opus-4-5-20250514", max_tokens=32000, thinking={ "type": "enabled", "budget_tokens": 25000 # Maximum budget for deep analysis }, system="""You are a senior technical analyst performing a comprehensive review. Use structured analysis templates and document all findings systematically.""", messages=[{ "role": "user", "content": "Perform a security threat model for..." }] )
Best Practices
- Use appropriate templates: Match template to analysis type
- Be systematic: Follow the template structure completely
- Quantify findings: Use metrics and severity ratings
- Prioritize actionable: Focus on findings that can be fixed
- Document evidence: Link to specific code/logs/data
- Track progress: Update findings as they're addressed
See Also
- [[extended-thinking]] - Enable deep reasoning capabilities
- [[complex-reasoning]] - Reasoning frameworks
- [[testing]] - Validation strategies
- [[debugging]] - Issue investigation
