gemini-skills: Skills for the Gemini API, SDK and model/agent interactions

by google-gemini · Agent Tool · ★ 4.4k

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

How to install gemini-skills

npx skills add google-gemini/gemini-skills --list
npx skills add google-gemini/gemini-skills --skill gemini-interactions-api

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

Security audit verdict: SAFE · quality 74/100

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.

geminigemini-apiskills

Quick Facts

Stars4,426
Forks487
LanguagePython
CategoryAgent Tool
LicenseApache-2.0
Quality Score74/100
Open Issues14
Last Updated2026-11-05
Created2026-02-06
Platformsgemini, python
Est. Tokens~14k

About gemini-skills

Gemini API skills A library of skills for the Gemini API, SDK and model interactions. About LLMs have fixed knowledge, being trained at a specific point in time. Software dev is fast paced and changes often, where new libraries are launched every day and best practices evolve quickly. This leaves a knowledge gap that language models can't solve on their own.

Compatible Skills

These tools work well together with gemini-skills for enhanced workflows:

  • antigravity-sdk-python — semantic(0.30)+complementary+same_lang+similar_pop+shared_platform (61%)
  • codebase-digest — semantic(0.27)+complementary+same_lang+similar_pop+shared_platform (60%)
  • AntiHub-ALL — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (58%)
  • NyaProxy — semantic(0.22)+complementary+same_lang+similar_pop+shared_platform (58%)

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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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