Generate Robust Swift Codable Models
A Swift Codable skill for robust JSON models - key mapping, safe defaults, partial-failure-tolerant arrays, and round-trip testing.
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Why it matters
Automate the creation of complex and maintainable Swift Codable models for efficient JSON parsing and serialization in your iOS and macOS applications.
Outcomes
What it gets done
Implement basic Codable structures with automatic JSON parsing.
Map snake_case API fields to camelCase Swift properties using CodingKeys.
Handle custom decoding logic, optional values, and default values.
Generate custom error handling and validation for decoding processes.
Install
Add it to your toolbox
Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/vb-swift-codable-model | bash After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.
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Overview
Swift Codable Model Expert
A Swift Codable skill for robust JSON models, covering key mapping, custom decoding, safe defaults, partial-failure-tolerant array decoding, and round-trip testing. Use it for the model and decoding layer of a Swift app working with real-world JSON APIs, not for URLSession networking or API-client architecture.
What it does
This is a Swift Codable skill for building robust JSON parsing and serialization models in iOS and macOS apps, covering basic struct conformance, CodingKeys for snake_case-to-camelCase API mapping, custom init(from decoder:) implementations for validation and transformation (including a generic APIResponse<T> wrapper that decodes a nullable nested payload and falls back to the current date if a timestamp string fails ISO8601 parsing), and property-wrapper-based default values - a @DefaultFalse wrapper that decodes a missing boolean field as false rather than failing. It centralizes decoder configuration in one reusable function:
func createJSONDecoder() -> JSONDecoder {
let decoder = JSONDecoder()
decoder.keyDecodingStrategy = .convertFromSnakeCase
decoder.dateDecodingStrategy = .iso8601
decoder.dataDecodingStrategy = .base64
return decoder
}
// Usage with error handling
func decode<T: Codable>(_ type: T.Type, from data: Data) -> Result<T, Error> {
let decoder = createJSONDecoder()
do {
let result = try decoder.decode(type, from: data)
return .success(result)
} catch {
return .failure(error)
}
}
When to use - and when NOT to
Use this skill when defining or hardening Codable models against real-world API responses that don't perfectly match Swift's defaults - missing fields, snake_case keys, nested optional data, or arrays that may contain a few malformed items, handled with a SafeArray wrapper that skips individual bad items via AnyCodable rather than failing the entire decode. It also covers a custom ModelDecodingError enum with LocalizedError conformance for meaningful debug messages, computed properties for values derived from decoded data (like an Order's subtotal, tax, and total), and a reusable XCTestCase extension that round-trips any Codable & Equatable model through encode-then-decode to assert equality. It is not a networking-layer skill - it's scoped to the model and decoding layer itself, so it isn't the right fit for URLSession request/response plumbing or API-client architecture.
Inputs and outputs
Input is raw JSON data, or an API's actual field names and structure; output is typed Swift structs conforming to Codable, using custom CodingKeys where the API's field names differ from Swift naming conventions, nested model hierarchies (a UserProfile example nests User, Account, and Permissions sub-structs, with an AccountType enum and its own CodingKeys for the permissions block), and a configured JSONDecoder applying .convertFromSnakeCase key decoding, .iso8601 date decoding, and .base64 data decoding consistently.
Integrations
Built entirely on Foundation's Codable, JSONDecoder/JSONEncoder, and ISO8601DateFormatter, plus XCTest for round-trip encode and decode testing.
Who it's for
iOS and macOS developers defining data models for JSON APIs who need consistent patterns for key mapping, safe defaults, partial-failure-tolerant array decoding, and testable round-trip encoding, rather than writing custom decoding logic ad hoc per model.
FAQ
Common questions
Discussion
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