Phase 1: Schema Design

Objective: Create a production-ready JSON schema respecting all limitations

Steps

1. Define Output Structure

Ask the user:

"What fields do you need in the output?"
"Which fields are required vs. optional?"
"What are the data types for each field?"
"Are there nested objects or arrays?"

2. Choose Schema Approach

Option A: Pydantic (Python) - Recommended

from pydantic import BaseModel
from typing import List, Optional

class ContactInfo(BaseModel):
    name: str
    email: str
    plan_interest: Optional[str] = None
    demo_requested: bool = False
    tags: List[str] = []

Option B: Zod (TypeScript) - Recommended

import { z } from 'zod';

const ContactInfoSchema = z.object({
  name: z.string(),
  email: z.string().email(),
  plan_interest: z.string().optional(),
  demo_requested: z.boolean().default(false),
  tags: z.array(z.string()).default([]),
});

Option C: Raw JSON Schema

{
  "type": "object",
  "properties": {
    "name": {"type": "string", "description": "Full name"},
    "email": {"type": "string", "description": "Email address"},
    "plan_interest": {"type": "string", "description": "Interested plan"},
    "demo_requested": {"type": "boolean"},
    "tags": {"type": "array", "items": {"type": "string"}}
  },
  "required": ["name", "email", "demo_requested"],
  "additionalProperties": false
}

3. Apply JSON Schema Limitations

✅ Supported Features:

All basic types: object, array, string, integer, number, boolean, null
enum (strings, numbers, bools, nulls only)
const
anyOf and allOf (limited)
$ref, $def, definitions (local only)
required and additionalProperties: false
String formats: date-time, time, date, email, uri, uuid, ipv4, ipv6
Array minItems (0 or 1 only)

❌ NOT Supported (SDK can transform these):

Recursive schemas
Numerical constraints (minimum, maximum)
String constraints (minLength, maxLength)
Complex array constraints
External $ref

4. Add AI-Friendly Descriptions

class Invoice(BaseModel):
    invoice_number: str  # Field(description="Invoice ID, format: INV-XXXXX")
    date: str  # Field(description="Invoice date in YYYY-MM-DD format")
    total: float  # Field(description="Total amount in USD")
    items: List[LineItem]  # Field(description="Line items on the invoice")

Good descriptions help Claude understand what to extract.

Output

Production-ready schema following Anthropic's limitations.

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