3.1 KiB
3.1 KiB
name, description
| name | description |
|---|---|
| json-outputs-implementer | Use PROACTIVELY when extracting structured data from text/images, classifying content, or formatting API responses with guaranteed schema compliance. Implements Anthropic's JSON outputs mode with Pydantic/Zod SDK integration. Covers schema design, validation, testing, and production optimization. Not for tool parameter validation or agentic workflows (use strict-tool-implementer instead). |
JSON Outputs Implementer
Overview
This skill implements Anthropic's JSON outputs mode for guaranteed schema compliance. With output_format, Claude's responses are validated against your schema—ideal for data extraction, classification, and API formatting.
What This Skill Provides:
- Production-ready JSON schema design
- SDK integration (Pydantic for Python, Zod for TypeScript)
- Validation and error handling patterns
- Performance optimization strategies
- Complete implementation examples
Prerequisites:
- Decision made via
structured-outputs-advisor - Model: Claude Sonnet 4.5 or Opus 4.1
- Beta header:
structured-outputs-2025-11-13
When to Use This Skill
Use for:
- Extracting structured data from text/images
- Classification tasks with guaranteed categories
- Generating API-ready responses
- Formatting reports with fixed structure
- Database inserts requiring type safety
NOT for:
- Validating tool inputs →
strict-tool-implementer - Agentic workflows →
strict-tool-implementer
Response Style
- Schema-first: Design schema before implementation
- SDK-friendly: Leverage Pydantic/Zod when available
- Production-ready: Consider performance, caching, errors
- Example-driven: Provide complete working code
- Limitation-aware: Respect JSON Schema constraints
Workflow
| Phase | Description | Details |
|---|---|---|
| 1 | Schema Design | → workflow/phase-1-schema-design.md |
| 2 | SDK Integration | → workflow/phase-2-sdk-integration.md |
| 3 | Error Handling | → workflow/phase-3-error-handling.md |
| 4 | Testing | → workflow/phase-4-testing.md |
| 5 | Production Optimization | → workflow/phase-5-production.md |
Quick Reference
Python Template
from pydantic import BaseModel
from anthropic import Anthropic
class MySchema(BaseModel):
field: str
response = client.beta.messages.parse(
model="claude-sonnet-4-5",
betas=["structured-outputs-2025-11-13"],
messages=[...],
output_format=MySchema,
)
result = response.parsed_output # Validated!
Supported Schema Features
✅ Basic types, enums, format strings, nested objects/arrays, required fields
❌ Recursive schemas, min/max constraints, string length, complex regex
Reference Materials
Related Skills
structured-outputs-advisor- Choose the right modestrict-tool-implementer- For tool validation use cases