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 calchiwo · Claude Skill · ★ 66
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ExplainThisRepo safe to install? View the security audit →
ExplainThisRepo The fastest way to understand any unfamiliar codebase using real project signals. Not blind AI guessing. Signals first. LLM second ExplainThisRepo analyzes real project signals; configs, entrypoints, manifests, dependencies graph, structures and high-signal files producing a clear, structured that shows you what the codebase actually does, how it is organized, where to start, what to ignore, and what matters before touching unfamiliar codebases.  designed to maximize AI agent per
Compile completed AI agent runs into reusable, cited context.
Don Cheli — SDD Framework. The most comprehensive Specification-Driven Development framework for AI agents. 88
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ExplainThisRepo is The fastest way to understand any codebase in plain English using real project signals. Not blind AI summarization. It is categorized as a Claude Skill with 66 GitHub stars.
ExplainThisRepo is primarily written in TypeScript. It covers topics such as calchiwo, claude-code, code-explainer.
You can find installation instructions and usage details in the ExplainThisRepo GitHub repository at github.com/calchiwo/ExplainThisRepo. The project has 66 stars and 9 forks, indicating an active community.
ExplainThisRepo is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ExplainThisRepo on Agent Skills Hub include aspens, codesyncer, AgentDeck. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
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.
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