technical-analysis
Technical analysis capabilities for APIs, data models, integrations, and security requirements. Use when analyzing technical aspects of systems or documenting technical requirements.
Best use case
technical-analysis is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Technical analysis capabilities for APIs, data models, integrations, and security requirements. Use when analyzing technical aspects of systems or documenting technical requirements.
Technical analysis capabilities for APIs, data models, integrations, and security requirements. Use when analyzing technical aspects of systems or documenting technical requirements.
Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.
Practical example
Example input
Use the "technical-analysis" skill to help with this workflow task. Context: Technical analysis capabilities for APIs, data models, integrations, and security requirements. Use when analyzing technical aspects of systems or documenting technical requirements.
Example output
A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.
When to use this skill
- Use this skill when you want a reusable workflow rather than writing the same prompt again and again.
When not to use this skill
- Do not use this when you only need a one-off answer and do not need a reusable workflow.
- Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/technical-analysis/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How technical-analysis Compares
| Feature / Agent | technical-analysis | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Technical analysis capabilities for APIs, data models, integrations, and security requirements. Use when analyzing technical aspects of systems or documenting technical requirements.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Technical Analysis Skill
## Overview
This skill provides techniques for analyzing technical aspects of software systems including APIs, data models, integrations, and security requirements.
## API Analysis
### REST API Analysis
#### Endpoint Discovery
Look for these patterns:
- Route definitions
- Controller classes
- OpenAPI/Swagger specifications
- API documentation
#### Endpoint Documentation Template
```markdown
### Endpoint: {METHOD} {PATH}
**Purpose**: {DESCRIPTION}
**Authentication**: {AUTH_METHOD}
**Request**:
- Headers: {HEADERS}
- Parameters: {PARAMS}
- Body: {BODY_SCHEMA}
**Response**:
- Success (200): {SUCCESS_SCHEMA}
- Error (4xx/5xx): {ERROR_SCHEMA}
**Business Rules**:
- {RULE_1}
- {RULE_2}
```
#### API Quality Checklist
- [ ] Consistent naming conventions
- [ ] Proper HTTP methods used
- [ ] Appropriate status codes
- [ ] Error responses standardized
- [ ] Pagination implemented for lists
- [ ] Versioning strategy in place
- [ ] Rate limiting configured
- [ ] Authentication documented
### GraphQL API Analysis
#### Schema Analysis
```graphql
type Query {
user(id: ID!): User
orders(userId: ID!, status: OrderStatus): [Order]
}
type Mutation {
createOrder(input: CreateOrderInput!): Order
updateOrderStatus(id: ID!, status: OrderStatus!): Order
}
```
#### Document
- Queries available (read operations)
- Mutations available (write operations)
- Types and their relationships
- Required vs optional fields
- Custom scalars
- Directives used
### Message/Event APIs
#### Event Schema Documentation
```markdown
### Event: {EVENT_NAME}
**Topic/Queue**: {TOPIC}
**Producer**: {PRODUCER_SERVICE}
**Consumers**: {CONSUMER_LIST}
**Payload Schema**:
{JSON_SCHEMA}
**Business Trigger**: {WHEN_PUBLISHED}
**Expected Response**: {CONSUMER_BEHAVIOR}
```
## Data Model Analysis
### Entity Analysis
#### Entity Documentation Template
```markdown
## Entity: {ENTITY_NAME}
### Description
{BUSINESS_DESCRIPTION}
### Attributes
| Name | Type | Required | Description | Constraints |
|------|------|----------|-------------|-------------|
| id | UUID | Yes | Primary key | Auto-generated |
| name | string | Yes | Display name | Max 100 chars |
| status | enum | Yes | Current state | Active, Inactive |
### Relationships
| Related Entity | Type | Description |
|---------------|------|-------------|
| Order | 1:N | Customer has many orders |
| Address | 1:1 | Customer has one address |
### Business Rules
- {RULE_1}
- {RULE_2}
### Indexes
| Index Name | Columns | Purpose |
|------------|---------|---------|
| idx_email | email | Unique lookup |
```
### Data Flow Analysis
#### Data Flow Documentation
```markdown
## Data Flow: {FLOW_NAME}
### Overview
{DESCRIPTION}
### Source
- System: {SOURCE_SYSTEM}
- Entity: {SOURCE_ENTITY}
- Trigger: {TRIGGER_EVENT}
### Transformations
1. {TRANSFORMATION_1}
2. {TRANSFORMATION_2}
### Destination
- System: {DEST_SYSTEM}
- Entity: {DEST_ENTITY}
- Action: {CREATE/UPDATE/DELETE}
### Error Handling
- {ERROR_SCENARIO}: {HANDLING}
### Diagram
[Source] → [Transform] → [Destination]
```
### Database Schema Analysis
#### Schema Documentation
```markdown
## Table: {TABLE_NAME}
### Columns
| Column | Type | Nullable | Default | Description |
|--------|------|----------|---------|-------------|
| id | bigint | No | auto | Primary key |
### Constraints
| Name | Type | Definition |
|------|------|------------|
| pk_table | Primary Key | (id) |
| fk_user | Foreign Key | user_id → users(id) |
| chk_status | Check | status IN ('A', 'I') |
### Indexes
| Name | Columns | Unique | Purpose |
|------|---------|--------|---------|
| idx_email | email | Yes | Lookup |
```
## Integration Analysis
### Integration Point Documentation
```markdown
## Integration: {INTEGRATION_NAME}
### Overview
| Attribute | Value |
|-----------|-------|
| External System | {SYSTEM_NAME} |
| Integration Type | API / File / Message Queue / Database |
| Direction | Inbound / Outbound / Bidirectional |
| Frequency | Real-time / Batch / Event-driven |
| Protocol | REST / SOAP / SFTP / MQ / etc. |
### Data Exchange
| Data Element | Source | Destination | Transform |
|--------------|--------|-------------|-----------|
| Customer ID | System A | System B | Direct map |
| Order Total | System A | System B | Convert currency |
### Authentication
- Method: {AUTH_METHOD}
- Credentials: {CREDENTIAL_LOCATION}
- Rotation: {ROTATION_POLICY}
### Error Handling
| Error Type | Detection | Response | Retry |
|------------|-----------|----------|-------|
| Timeout | 30s limit | Log + Alert | 3x exponential |
| 4xx Error | Response code | Log + Skip | No retry |
| 5xx Error | Response code | Log + Alert | 3x exponential |
### SLA
- Availability: {UPTIME_REQUIREMENT}
- Response Time: {LATENCY_REQUIREMENT}
- Throughput: {VOLUME_REQUIREMENT}
### Monitoring
- Health Check: {ENDPOINT}
- Metrics: {METRICS_COLLECTED}
- Alerts: {ALERT_CONDITIONS}
```
### Integration Pattern Analysis
#### Synchronous Patterns
- **Request-Response**: Direct API calls
- **API Gateway**: Centralized routing
- **Service Mesh**: Sidecar proxies
#### Asynchronous Patterns
- **Message Queue**: Point-to-point messaging
- **Publish-Subscribe**: Event distribution
- **Event Sourcing**: Event log as source of truth
#### Data Integration Patterns
- **ETL**: Extract, Transform, Load
- **Change Data Capture**: Real-time sync
- **Data Virtualization**: On-demand access
## Security Analysis
### Security Requirements Documentation
#### Authentication Analysis
```markdown
## Authentication
### Current Implementation
- Method: {JWT / OAuth2 / SAML / etc.}
- Identity Provider: {IDP_NAME}
- Token Lifetime: {DURATION}
- Refresh Strategy: {STRATEGY}
### Multi-Factor Authentication
- Required For: {USER_TYPES}
- Methods: {MFA_METHODS}
- Bypass Conditions: {EXCEPTIONS}
### Session Management
- Timeout: {IDLE_TIMEOUT}
- Concurrent Sessions: {ALLOWED / PREVENTED}
- Session Storage: {MECHANISM}
```
#### Authorization Analysis
```markdown
## Authorization
### Access Control Model
- Type: RBAC / ABAC / ACL / Custom
### Roles
| Role | Description | User Count |
|------|-------------|------------|
| Admin | Full access | 5 |
| Manager | Department access | 20 |
| User | Limited access | 500 |
### Permissions Matrix
| Resource | Admin | Manager | User |
|----------|-------|---------|------|
| Users | CRUD | R | - |
| Orders | CRUD | CRUD | CRU |
| Reports | CRUD | R | R |
### Business Rules
- {RULE_1}
- {RULE_2}
```
#### Data Protection Analysis
```markdown
## Data Protection
### Sensitive Data Inventory
| Data Element | Classification | Protection |
|--------------|----------------|------------|
| Password | Secret | Hashed (bcrypt) |
| SSN | PII | Encrypted at rest |
| Credit Card | PCI | Tokenized |
### Encryption
- At Rest: {METHOD}
- In Transit: {METHOD}
- Key Management: {STRATEGY}
### Data Masking
| Field | Mask Type | Example |
|-------|-----------|---------|
| SSN | Partial | ***-**-1234 |
| Email | Partial | j***@***.com |
```
### Compliance Analysis
```markdown
## Compliance Requirements
### Applicable Regulations
| Regulation | Scope | Requirements |
|------------|-------|--------------|
| GDPR | EU users | Consent, Right to erasure |
| HIPAA | Health data | PHI protection |
| PCI-DSS | Payment data | Card data security |
### Compliance Controls
| Control | Implementation | Evidence |
|---------|----------------|----------|
| Access logging | Audit table | Logs |
| Encryption | AES-256 | Config |
| Retention | 7 years | Policy doc |
### Audit Requirements
- Audit logging enabled: {YES/NO}
- Retention period: {DURATION}
- Access review frequency: {FREQUENCY}
```
## Infrastructure Analysis
### Infrastructure Documentation
```markdown
## Infrastructure Overview
### Environments
| Environment | Purpose | URL |
|-------------|---------|-----|
| Development | Dev testing | dev.app.com |
| Staging | Pre-prod testing | staging.app.com |
| Production | Live system | app.com |
### Compute
| Component | Type | Specs | Count |
|-----------|------|-------|-------|
| Web Server | VM/Container | 4 CPU, 8GB | 3 |
| API Server | Container | 2 CPU, 4GB | 5 |
| Database | RDS | db.r5.large | 2 |
### Networking
- VPC/VNET: {NETWORK_ID}
- Subnets: {SUBNET_LIST}
- Load Balancer: {LB_TYPE}
- CDN: {CDN_PROVIDER}
### Storage
| Type | Purpose | Size | Backup |
|------|---------|------|--------|
| RDS | Primary DB | 500GB | Daily |
| S3 | File storage | 1TB | Cross-region |
| Redis | Cache | 10GB | None |
```
## Analysis Output Summary
After technical analysis, document:
1. **API Contracts**: All endpoints with schemas
2. **Data Models**: Entities, relationships, constraints
3. **Integrations**: External systems, data flows
4. **Security**: Auth, authorization, data protection
5. **Infrastructure**: Compute, storage, networking
6. **Technical Debt**: Issues and recommendations
See [integration-patterns.md](integration-patterns.md) for common integration patterns.Related Skills
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