When designing and implementing web interfaces to ensure they are usable by everyone.
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When creating or extending an HTTP API for client consumption.
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REST APIs MUST be intuitive, predictable, and semantically correct. This skill ensures APIs use HTTP methods correctly, communicate errors clearly via standard formats, and maintain consistency across resources so clients can interact with them reliably without surprise behavior.
/users/{id}/orders ONLY)limit and offset (or cursor-based pagination)/v1/ prefix or header-based versioning from day oneGET /getUsers)GET /getUsers, POST /createOrder (use nouns + HTTP methods){ status: 'error' } payload (use 4xx/5xx status codes)/companies/{id}/departments/{id}/employees/{id}/tasks (use max 2 levels)/api/users without versioning path for future breaking changestype, title, detail, statuslimit and offset parameters/v1/users or header-based)/user-profiles not /userProfiles)type, title, detail, status, instance)limit, offset, total in collection response envelope/v1/ URL prefix or API-Version: 1.0 headerlimit=999999999)❌ Anti-pattern (Verbs in URL, wrong status codes, deep nesting, no pagination):
GET /api/getUsers HTTP/1.1
HTTP/1.1 200 OK
{
"status": "error",
"message": "User not found"
}
GET /api/companies/123/departments/456/employees/789/tasks/assignToUser HTTP/1.1
✅ Correct pattern (Nouns, semantic status, proper nesting, paginated):
GET /v1/users?limit=20&offset=0 HTTP/1.1
HTTP/1.1 200 OK
{
"data": [...],
"pagination": {
"limit": 20,
"offset": 0,
"total": 150
}
}
GET /v1/users/123 HTTP/1.1
HTTP/1.1 404 Not Found
{
"type": "https://api.example.com/errors/resource-not-found",
"title": "Resource Not Found",
"detail": "The requested user does not exist",
"status": 404,
"instance": "/v1/users/123"
}
GET /v1/users/123/orders?limit=10&offset=0 HTTP/1.1
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When designing and implementing web interfaces to ensure they are usable by everyone.
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When improving read performance and reducing database load.
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When configuring automated build, test, and deployment workflows for a repository.
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When asynchronously reviewing peer code before merging into the main branch.
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When addressing slow application endpoints, high database CPU usage, or standardizing data access patterns.
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When isolating and fixing unpredictable or complex software bugs.
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