unifai-sdk-py: Python SDK for Unifai, an AI native platform for dynamic tools and agent to agent communication

by unifai-network · Agent Tool · ★ 140

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

Security audit verdict: SAFE · quality 70/100

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

Stars140
Forks25
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score70/100
Last Updated2026-01-26
Created2025-01-16
Platformspython
Est. Tokens~44k

About unifai-sdk-py

unifai-sdk-py unifai-sdk-py is the Python SDK for UnifAI, an AI native platform for dynamic tools and agent to agent communication. Installation Getting your UnifAI API key You can get your API key for free from UnifAI Console. There are two types of API keys: Agent API key: for using toolkits in your own agents. Toolkit API key: for creating toolkits that can be used by other agents.

Compatible Skills

These tools work well together with unifai-sdk-py for enhanced workflows:

  • acodex — semantic(0.29)+complementary+same_lang+similar_pop+shared_platform (55%)
  • mkinf — semantic(0.28)+complementary+same_lang+similar_pop+shared_platform (55%)
  • quant-python-ai — semantic(0.25)+complementary+same_lang+similar_pop+shared_platform (54%)
  • openai-agents-demos — semantic(0.21)+complementary+same_lang+similar_pop+shared_platform (52%)

unifai-sdk-py alternative? Top 1 similar tools

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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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