System Documentation

What problem does it solve?

Semantic Gradient Optimization (SGO) enables you to measure how an entity you control is perceived by a diverse evaluator population, and to discover targeted changes that move that perception toward a defined goal.

Core Features & Use Cases

  • Build a realistic evaluator panel using census-grounded Nemotron personas or LL-generated cohorts
  • Score the entity with LLM-based evaluations and derive a semantic gradient via counterfactual probes
  • Prioritize changes and simulate outcomes across audience segments, with optional goal weighting

Quick Start

Describe your entity and goal, assemble or load an evaluator cohort, run the evaluation, and review the semantic gradient to identify the top changes.

Dependency Matrix

Required Modules

datasetshuggingface_hubopenaipython-dotenvfastapiuvicornsse-starlette

Components

scripts

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: sgo
Download link: https://github.com/xuy/sgo/archive/main.zip#sgo

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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