Deep Analysis Skill
Comprehensive analytical templates for thorough investigation, audits, and evaluations leveraging extended thinking capabilities.
When to Use
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Code audits requiring systematic review
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Security assessments and threat modeling
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Performance analysis and optimization planning
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Architecture reviews and technical debt assessment
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Incident post-mortems and root cause analysis
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Compliance audits and risk assessments
Analysis Templates
Code Audit Template
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
- Immediate: [Critical fixes]
- Short-term: [Within sprint]
- 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
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
- 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
- [Priority 1 recommendations]
- [Priority 2 recommendations]
- [Priority 3 recommendations]
Performance Analysis Template
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
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Database Queries (High Impact)
- Location:
/api/searchendpoint - Cause: Missing index on
created_atcolumn - Impact: 890ms P95 latency
- Fix: Add composite index
- Location:
-
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)
- Add database indexes - Expected: 40% improvement
- Enable query caching - Expected: 25% improvement
- Optimize N+1 queries - Expected: 30% improvement
Medium Term (Next Quarter)
- Implement read replicas
- Add CDN for static assets
- Optimize serialization
Long Term (6+ Months)
- Service decomposition
- Event-driven architecture
- 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
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
- User request → API Gateway
- API Gateway → Auth validation
- Auth → Core API
- Core API → Database
- 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)
- [Recommendation 1]
- [Recommendation 2]
Short-term (3-6 months)
- [Recommendation 1]
- [Recommendation 2]
Long-term (6-12 months)
- [Recommendation 1]
- [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:
response = 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
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Use appropriate templates: Match template to analysis type
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Be systematic: Follow the template structure completely
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Quantify findings: Use metrics and severity ratings
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Prioritize actionable: Focus on findings that can be fixed
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Document evidence: Link to specific code/logs/data
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Track progress: Update findings as they're addressed
See Also
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[[extended-thinking]] - Enable deep reasoning capabilities
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[[complex-reasoning]] - Reasoning frameworks
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[[testing]] - Validation strategies
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[[debugging]] - Issue investigation