shuxiachai

Academic Commercialization Agent — AI skill for Claude Code

AI community

Turn any research paper into a commercialization report — 6 AI agents, TRL/MRL scoring, patent landscape, market intelligence, verified citations.

How to install Academic Commercialization Agent

This entry records only its repository, not the path inside it, so there is no exact command to give. Open shuxiachai/academic-commercialization-agent and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Academic Commercialization Agent does

Turn any research paper into a commercialization report — 6 AI agents, TRL/MRL scoring, patent landscape, market intelligence, verified citations. DeepSeek / OpenAI / Claude.

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README

Academic Commercialization Assessment Agent

**Turn any research paper or topic into a commercialization readiness report in minutes** — six AI agents gather academic, patent, and market evidence, then produce a scored report with verifiable citations.

[![Tests](https://github.com/shuxiachai/academic-commercialization-agent/actions/workflows/test.yml/badge.svg)](https://github.com/shuxiachai/academic-commercialization-agent/actions/workflows/test.yml) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE) [![Python 3.11+](https://img.shields.io/badge/python-3.11%2B-blue.svg)](https://www.python.org/downloads/) [![CrewAI](https://img.shields.io/badge/CrewAI-1.14.x-orange.svg)](https://github.com/crewAIInc/crewAI)

[![Live demo](https://img.shields.io/badge/live%20demo-try%20it-brightgreen.svg)](https://academic-commercialization-agent.up.railway.app)

[Portfolio case study](docs/portfolio-case-study.md) | [90-second demo guide](docs/demo-script-90s.md) | [v2.0.0 release notes](docs/release-v2.0.0.md)

[English](#english) | [中文](#chinese)

English

A multi-agent system built on [CrewAI](https://github.com/crewAIInc/crewAI) that evaluates the commercialization readiness of academic research.

Input a research direction or paper topic. Six specialized AI agents automatically gather evidence from academic literature, patent databases, and market intelligence sources, then produce a structured commercialization assessment report with verifiable citations and a quantitative scorecard.

An optional Decision Context adds the asset, application, decision owner and decision being considered. Topic-only and partial-context runs remain valid, but explicitly stay in orientation mode instead of presenting actor-specific GO/NO_GO advice as if the missing decision boundary had been established.