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 ChinaSiro · AI Tool · ★ 9.7k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is claude-code-sourcemap safe to install? View the security audit →
claude-code-sourcemap [!WARNING] This repository is unofficial and is reconstructed from the public npm package and source map analysis, for research purposes only. It does not represent the original internal development repository structure. 本仓库为非官方整理版，基于公开 npm 发布包与 source map 分析还原，仅供研究使用。 不代表官方原始内部开发仓库结构。 一切基于L站"飘然与我同"的情报提供 概述 本仓库通过 npm 发布包（）内附带的 source map（）还原的 TypeScript 源码，版本为 。 来源 npm 包：@anthropic-ai/claude-code 还原版本： 还原文件数：4756 个（含 1884 个 / 源文件） 还原方式：提取 中的 字段 目录结构 声明 源码版权归 Anthropic 所有 本仓库仅用于技术研究与学习，请勿用于
| Stars | 9,696 |
| Forks | 14,576 |
| Language | TypeScript |
| Category | AI Tool |
| Quality Score | 41.6091922890296/100 |
| Open Issues | 15 |
| Last Updated | 2026-03-31 |
| Created | 2026-03-31 |
| Platforms | claude-code, node |
| Est. Tokens | ~14k |
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claude-code-sourcemap is an open-source ai tool by ChinaSiro with 9.7k GitHub stars.
claude-code-sourcemap is primarily written in TypeScript.
You can find installation instructions and usage details in the claude-code-sourcemap GitHub repository at github.com/ChinaSiro/claude-code-sourcemap. The project has 9.7k stars and 14576 forks, indicating an active community.
The top alternatives to claude-code-sourcemap on Agent Skills Hub include claude-code-infrastructure-showcase, vision-agent, axton-obsidian-visual-skills. 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.
Sources & who's responsible: