X-Master: Official implementation of X-Master, a general-purpose tool-augmented reasoning agent

by sjtu-sai-agents · Agent Tool · ★ 323

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

Security audit verdict: SAFE · quality 63/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

Quick Facts

Stars323
Forks25
LanguagePython
CategoryAgent Tool
Quality Score63/100
Open Issues11
Last Updated2025-10-18
Created2025-07-06
Platformspython
Est. Tokens~60k

About X-Master

X-Master: Can We Lead on Humanity’s Last Exam? 📑 ArXiv Paper 🔥 News [2025/08/22] Initial codes of X-Master is now available on GitHub! [2025/07/26] Play with our SciMaster, a general-purpose scientific AI agent product! This is the official implementation of X-Master, a general-purpose tool-augmented reasoning agent.

Compatible Skills

These tools work well together with X-Master for enhanced workflows:

  • AIlice — semantic(0.43)+complementary+same_lang+similar_pop+shared_platform (60%)
  • ai-manus — semantic(0.37)+complementary+same_lang+similar_pop+shared_platform (58%)
  • NexAU — semantic(0.35)+complementary+same_lang+similar_pop+shared_platform (57%)
  • EnvScaler — semantic(0.29)+complementary+same_lang+similar_pop+shared_platform (55%)
  • raptor — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (53%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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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