academic-commercialization-agent — security grade SAFE, quality 67/100

Security audit verdict: SAFE · quality 67/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by shuxiachai · Agent Tool · ★ 812

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is academic-commercialization-agent safe to install? View the security audit →

About academic-commercialization-agent

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. English | 中文 English A multi-agent system built on 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. Screenshots ▶ Analysis in progress — live agent status + source list <img src

academic-researchai-agentanthropiccommercializationcrewaideepseekgradiollmmulti-agentopenai

Quick Facts

Stars812
Forks101
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score66.9632152900827/100
Open Issues2
Last Updated2026-09-17
Created2026-06-25
Platformspython
Est. Tokens~20k

Compatible Skills

These tools work well together with academic-commercialization-agent for enhanced workflows:

  • PatentRadar — semantic(0.34)+complementary+shared_fw(openai)+rare_topics+same_lang+similar_pop+shared_platform (74%)
  • Codex-Academic-Skills — semantic(0.19)+complementary+shared_fw(openai)+rare_topics+same_lang+similar_pop+shared_platform (69%)
  • AlterLab-Academic-Skills — semantic(0.23)+complementary+rare_topics+same_lang+similar_pop+shared_platform (67%)

academic-commercialization-agent alternative? Top 6 similar tools

Looking for a academic-commercialization-agent alternative? If you're comparing academic-commercialization-agent with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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Frequently Asked Questions

What is academic-commercialization-agent?

academic-commercialization-agent is Evidence-constrained commercialization assessment with deterministic retrieval, six LLM stages, auditable scoring and checkpoint recovery.. It is categorized as a Agent Tool with 812 GitHub stars.

What programming language is academic-commercialization-agent written in?

academic-commercialization-agent is primarily written in Python. It covers topics such as academic-research, ai-agent, anthropic.

How do I install or use academic-commercialization-agent?

You can find installation instructions and usage details in the academic-commercialization-agent GitHub repository at github.com/shuxiachai/academic-commercialization-agent. The project has 812 stars and 101 forks, indicating an active community.

What license does academic-commercialization-agent use?

academic-commercialization-agent is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to academic-commercialization-agent?

The top alternatives to academic-commercialization-agent on Agent Skills Hub include captain-claw, antigravity-workspace-template, autollm. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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