codexkit-api-design-reviewer

name	codexkit-api-design-reviewer
description	Review REST and GraphQL API designs for consistency, usability, and best practices. Covers naming conventions, versioning strategy, error format, pagination, authentication patterns, and breaking change detection. Use when reviewing API specs, designing new APIs, or auditing existing endpoints.
version	1.0.0
category	review

API Design Reviewer

When to Use

• When reviewing an OpenAPI/Swagger specification before implementation
• When auditing existing API endpoints for consistency
• When designing a new API from scratch
• When preparing APIs for external/partner consumption

Procedure

Step 1 — Naming & Convention Check

Check	Rule	Example
Resource naming	Plural nouns, kebab-case	✅ /api/v1/order-items ❌ /api/v1/getOrderItem
HTTP methods	GET=read, POST=create, PUT=replace, PATCH=partial, DELETE=remove	✅ POST /orders ❌ POST /create-order
Query params	camelCase for filters/sorting	✅ ?sortBy=createdAt ❌ ?sort_by=created_at
Status codes	Use standard codes correctly	✅ 201 Created, 204 No Content ❌ 200 for everything
Consistency	Same pattern across all endpoints	Check all resources follow same naming

Step 2 — Versioning Strategy

Strategy	When to Use	Pattern
URL path	Simple, widely adopted	/api/v1/orders
Header	Cleaner URLs, harder to test	Accept: application/vnd.api+json;version=1
Query param	Easy to test, but less RESTful	/api/orders?version=1

Verify:

• Version is present in all endpoints
• Deprecation policy documented
• Migration guide for version bumps

Step 3 — Error Format

Errors should follow a consistent structure:

{
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Human-readable description",
    "details": [
      {
        "field": "email",
        "issue": "Invalid format",
        "expected": "Valid email address"
      }
    ],
    "request_id": "req_abc123",
    "docs_url": "https://docs.api.com/errors/VALIDATION_ERROR"
  }
}

Check:

• Error format consistent across all endpoints
• Machine-readable error codes (not just messages)
• Request ID for traceability
• No sensitive data in error responses

Step 4 — Pagination

Pattern	Best For	Implementation
Cursor-based	Large datasets, real-time data	?cursor=abc&limit=20
Offset-based	Simple lists, admin UIs	?page=2&per_page=20
Keyset	Time-series data	?after=2024-03-15T00:00:00Z&limit=20

Check:

• Default page size set (and documented)
• Maximum page size enforced
• Total count available (or explicitly omitted for performance)
• Links to next/prev pages in response

Step 5 — Security Patterns

Check	Details
Authentication	Bearer token, API key, OAuth2 — documented per endpoint
Authorization	Role-based access noted per endpoint
Rate limiting	Headers: X-RateLimit-Limit, X-RateLimit-Remaining, Retry-After
Input validation	Max lengths, allowed characters, type checking
CORS	Appropriate origins, methods, headers

Step 6 — Breaking Change Detection

Identify potential breaking changes:

• ❌ Removing a field from response
• ❌ Changing a field type (string → integer)
• ❌ Making an optional field required
• ❌ Changing endpoint URL
• ✅ Adding a new optional field
• ✅ Adding a new endpoint
• ✅ Adding a new optional query parameter

Inputs

Input	Required	Format
API specification	Yes	OpenAPI/Swagger YAML/JSON or endpoint list
Business context	Recommended	Who consumes this API
Existing API	Recommended	For breaking change detection

Output

## API Review — [API Name]

### Summary
**Endpoints reviewed:** 24 | **Issues found:** 8 | **Breaking changes:** 0

### Issues

| # | Severity | Category | Endpoint | Issue | Fix |
|---|----------|----------|----------|-------|-----|
| 1 | High | Naming | POST /createUser | Verb in URL | POST /users |
| 2 | Medium | Errors | All | No request_id | Add tracing ID |
| 3 | Low | Pagination | GET /logs | No max page size | Enforce limit ≤ 100 |

### Recommendations
[Summary of patterns to adopt or fix]

Definition of Done

• Naming conventions checked across all endpoints
• Versioning strategy reviewed
• Error format consistency verified
• Pagination patterns assessed
• Security patterns checked
• Breaking changes flagged

Quality Criteria

• Feedback is specific and references exact locations in the reviewed material
• Each critique includes a concrete improvement suggestion
• Severity is categorized (critical / important / nice-to-have)
• Positive aspects are acknowledged alongside areas for improvement

Verification (4C)

Check	Question
Correctness	Is the feedback technically accurate and properly contextualized?
Completeness	Were all major sections of the reviewed material addressed?
Context-fit	Is the review granularity appropriate for the material's maturity level?
Consequence	If the author implemented all feedback literally, what could go wrong?

Edge Cases

• Material is too early-stage for detailed review — Provide structural feedback only. Note that content review is deferred until it matures.
• Reviewer lacks domain expertise — Focus on structure, clarity, and consistency. Flag domain-specific claims as 'Needs SME verification'.
• Author is defensive or resistant to feedback — Lead with what works well. Frame changes as questions rather than mandates.

Changelog

• v1.0.0 — Initial release