brag-codex — security grade SAFE, quality 64/100

Security audit verdict: SAFE · quality 64/100

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 mattivilola · Codex Skill · ★ 32

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

🔒 Is brag-codex safe to install? View the security audit →

About brag-codex

Codex-compatible clone of latent-spaces/brag for Hyperframes launch videos

Quick Facts

Stars32
Forks6
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score63.7214034651117/100
Last Updated2026-06-23
Created2026-06-23
Platformscodex, python
Est. Tokens~14k

Compatible Skills

These tools work well together with brag-codex for enhanced workflows:

  • saas-motion-kit — semantic(0.27)+complementary+same_lang+similar_pop+shared_platform (59%)
  • avatar-mix — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (58%)

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Frequently Asked Questions

What is brag-codex?

brag-codex is Codex-compatible clone of latent-spaces/brag for Hyperframes launch videos. It is categorized as a Codex Skill with 32 GitHub stars.

What programming language is brag-codex written in?

brag-codex is primarily written in Python.

How do I install or use brag-codex?

You can find installation instructions and usage details in the brag-codex GitHub repository at github.com/mattivilola/brag-codex. The project has 32 stars and 6 forks, indicating an active community.

What license does brag-codex use?

brag-codex is released under the MIT license, making it free to use and modify according to the license terms.

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:

View on GitHub → Browse Codex Skill tools