Design Schema-Guided Reasoning pipelines that translate expert checklists into structured LLM reasoning.
npx skills add https://github.com/fortunto2/solo-factory --skill solo-sgr
Please help me install this Agent Skill. Skill: solo-sgr Source: https://github.com/fortunto2/solo-factory/tree/main/skills/sgr Command: npx skills add https://github.com/fortunto2/solo-factory --skill solo-sgr
Design and implement Schema-Guided Reasoning (SGR) pipelines that translate domain expert checklists into structured, automatable reasoning for LLMs, enabling predictable, auditable agent behavior.
Define a minimal SGR workflow with a NextStep-based schema and dispatch a tool in response to the first planning step.
High-intent search queries and answers about installing and using this skill.
You can enforce structured output by defining Schema-Guided Reasoning pipelines that use Pydantic-based schemas and discriminated unions to constrain LLM decoding, ensuring predictable and auditable agent behavior.
Deterministic tool routing is achieved by applying agent loop patterns like NextStep and Tool Dispatch, which use strict schemas to guide LLM reasoning and automate tool selection based on the planning step.
Translate expert checklists into automatable reasoning by designing SGR pipelines that enforce reasoning steps, order, and focus using tight Pydantic type constraints, yielding verifiable and auditable outputs.
Yes, you can use Pydantic discriminated unions to route and validate structured analysis across compliance contexts, ensuring LLM outputs adhere to strict schemas and enabling safe, auditable prompts.
Yes, Pydantic schemas are required to build an Analysis Cascade, providing the tight type constraints necessary to validate intermediate reasoning steps and ensure verifiable outputs across the pipeline.
Schema-guided reasoning requires strict schema definitions and tight type constraints, meaning any deviation from the defined Pydantic models or unsupported tool dispatch patterns will cause validation failures in the pipeline.
compozyValidate runtime data with Zod schemas using safeParse and error handling.
mealpacDispatch autonomous subagents to execute implementation tasks with two-stage reviews.
andrueandersoncsIntegrate and orchestrate AI/LLM services with Effect-TS using type-safe providers and tooling.
bmsull560Validate LLM outputs against Pydantic schemas with function calling.
