What does the configSchema enforce?

It enforces a strict object structure with nested sections like server and logging, including required types (e.g., host as string, port as int) and sensible defaults.

How are defaults handled?

Defaults are specified with default() for individual fields and default({}) for nested objects; getConfigWithDefaults(partial) applies these defaults by parsing the partial input.

How can I extend the schema for more config sections?

Add fields to configSchema, update the exported Config type accordingly, and consider whether to keep .strict() to disallow extra keys; add tests for new sections.

config-schema-validator

Scanned

npx machina-cli add skill a5c-ai/babysitter/config-schema-validator --openclaw

Files (1)

SKILL.md

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Config Schema Validator

Generate configuration schema validators.

Generated Patterns

import { z } from 'zod';

export const configSchema = z.object({
  server: z.object({
    host: z.string().default('localhost'),
    port: z.number().int().min(1).max(65535).default(3000),
    cors: z.object({
      origins: z.array(z.string().url()).default(['*']),
      credentials: z.boolean().default(false),
    }).default({}),
  }).default({}),
  logging: z.object({
    level: z.enum(['debug', 'info', 'warn', 'error']).default('info'),
    format: z.enum(['json', 'pretty']).default('pretty'),
  }).default({}),
}).strict();

export type Config = z.infer<typeof configSchema>;

export function validateConfig(input: unknown): Config {
  return configSchema.parse(input);
}

export function getConfigWithDefaults(partial: Partial<Config> = {}): Config {
  return configSchema.parse(partial);
}

Target Processes

configuration-management-system
mcp-tool-implementation
cli-application-bootstrap

Source

git clone https://github.com/a5c-ai/babysitter/blob/main/plugins/babysitter/skills/babysit/process/specializations/cli-mcp-development/skills/config-schema-validator/SKILL.md

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Overview

Config Schema Validator generates strict, typed validators for app configuration using Zod (and JSON Schema patterns). It provides a ready-to-use configSchema with nested sections like server and logging, each with sensible defaults, and helper functions to validate input or generate a config with defaults. This ensures runtime config integrity and clearer error messages.

How This Skill Works

It defines a Zod schema (configSchema) with nested objects (server, logging, etc.), uses default() to supply defaults, and .strict() to forbid unknown keys. It exports a Config type inferred from the schema and two helpers: validateConfig(input) which parses and validates input, and getConfigWithDefaults(partial) which fills in missing fields via the schema defaults.

When to Use It

When building a CLI tool that reads config from a file or environment variables
During development of a configuration-management system requiring strict validation
When bootstrapping an MCP tool or CLI app and needing sensible defaults
If you want to enforce constraints on server.host, server.port, and CORS settings
To catch configuration errors early with clear, schema-driven error messages

Quick Start

Step 1: Import { configSchema, validateConfig, getConfigWithDefaults } from the skill
Step 2: Use validateConfig(input) to parse and validate user config
Step 3: Use getConfigWithDefaults(partial) to apply defaults for missing fields

Best Practices

Keep the schema as the single source of truth and export the Config type
Use default() on fields to provide safe, predictable defaults
Call .strict() to disallow unknown keys and surface misconfigurations
Document and standardize error messages returned by validation
Write tests that cover both valid configurations and common invalid cases

Example Use Cases

Configuring server settings with host, port, and cors origins using the configSchema
Defining logging settings with level and format and default values
Validating a partial config with getConfigWithDefaults to fill in missing fields
Parsing user-provided config.json into the Config type via validateConfig
Integrating into configuration-management-system and mcp-tool-implementation workflows

Frequently Asked Questions

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