natively-cluely-ai-assistant: Natively — Free open-source AI meeting assistant, interview copilot, and note taker

by Natively-AI-assistant · Claude Skill · ★ 3.2k

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

How to install natively-cluely-ai-assistant

git clone https://github.com/evinjohnn/natively-cluely-ai-assistant.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 59/100

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. Full audit →

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.

aiai-agentai-agentsai-assistantai-toolscheatingclaude-codeclaude-skillscluelycluely-alternative

Quick Facts

Stars3,197
Forks673
LanguageTypeScript
CategoryClaude Skill
Quality Score59/100
Open Issues74
Last Updated2026-11-06
Created2026-01-27
Platformsclaude-code, node
Est. Tokens~25k

About natively-cluely-ai-assistant

Natively — Free, Open-Source AI Interview Copilot & Meeting Assistant The best free alternative to Cluely, Final Round AI, LockedIn AI, and Interview Coder. Same UI as Cluely. More features. $0. Open source. No data breaches.

Compatible Skills

These tools work well together with natively-cluely-ai-assistant for enhanced workflows:

  • project-raven — semantic(0.21)+complementary+same_lang+similar_pop+shared_platform (57%)
  • minutes — semantic(0.16)+complementary+similar_pop+shared_platform (46%)

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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:

View on GitHub → Browse Claude Skill tools