ip-as-logo-skill: A compact Agent Skill for highly simplified, rounded, subtly neo-skeuomorphic IP mascot logos

by s1dashu · Codex Skill · ★ 3.8k

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

How to install ip-as-logo-skill

npx skills@latest add s1dashu/ip-as-logo-skill
npx skills@latest add s1dashu/ip-as-logo-skill --global

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

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. 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.

codexcodex-skillimage-generationlogo-designmascot-design

Quick Facts

Stars3,782
Forks180
CategoryCodex Skill
LicenseMIT
Quality Score70/100
Open Issues4
Last Updated2026-08-22
Created2026-08-18
Platformscodex
Est. Tokens~17k

About ip-as-logo-skill

IP as Logo is a compact Agent Skill for generating highly simplified personified mascot logos. It treats the result as a logo first and a character second: bold rounded silhouettes, strict complexity limits, oversized corner composition, and extremely subtle neo-skeuomorphic shading.

Compatible Skills

These tools work well together with ip-as-logo-skill for enhanced workflows:

  • codex-hygiene — semantic(0.34)+complementary+similar_pop+shared_platform (52%)

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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 Codex Skill tools