get-it: Read it. See it. Get it. Built at GDG AI Hack Milan 2026 for Learn Different track

Last updated: 2026-06-29 · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install get-it

git clone https://github.com/beltromatti/get-it.git

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

Security audit verdict: SAFE · quality 69/100

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.

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Quick Facts

Stars	906
Forks	109
Language	JavaScript
Category	Codex Skill
License	Apache-2.0
Quality Score	69/100
Open Issues	5
Last Updated	2026-06-29
Created	2026-05-09
Platforms	codex, node
Est. Tokens	~16k

About get-it

Get It. Read it. See it. Get it. The study companion that turns a PDF into a measurable mastery map. Built around the document, not in place of it. [![TypeScript](https://img.shields.io/badge/TypeScript-5.x-

Compatible Skills

These tools work well together with get-it for enhanced workflows:

learn-faster-kit — semantic(0.38)+complementary+rare_topics+similar_pop (57%)
Bloom — semantic(0.18)+complementary+rare_topics+similar_pop (50%)
vestige — semantic(0.23)+complementary+rare_topics+similar_pop (47%)
human-skill-tree — semantic(0.21)+complementary+rare_topics+similar_pop+shared_platform (47%)

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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