structured-output

What problem does it solve?

LLMs often produce free-form text, making it challenging to reliably extract structured data for downstream processing or database integration. This Skill ensures LLM outputs conform to a defined schema, eliminating manual parsing and validation.

Core Features & Use Cases

• Unified JSON Schema: Define desired output structures using standard JSON Schema, automatically adapted for all major LLM providers (OpenAI, Anthropic, Google, Ollama).
• Automatic Validation & Parsing: Receive pre-parsed Python dictionaries, guaranteed to match your schema, reducing parsing errors and development time.
• Strict Mode Enforcement: Ensure LLM outputs strictly adhere to the schema, preventing unexpected data formats and improving data quality.
• Use Case: Extract customer contact information (name, age, email) from unstructured text, classify sentiment with a confidence score, or generate complex nested JSON objects for API responses, all with guaranteed structural integrity.

Quick Start

Use the structured-output skill to generate a 'person' object with 'name', 'age', and 'email' fields, ensuring the output is strictly validated JSON.