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 JamesShi96 · Claude Skill · ★ 372
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is project-butler safe to install? View the security audit →
project-butler English | 中文 Persistent project memory for AI coding assistants. project-butler gives Claude Code, Cursor, Codex, and similar AI coding assistants a shared project memory stack: session logs, handoff notes, project wiki, TODOs, rules, file structure, and changelog. You keep working normally. At the end, say . Next time, say . Quick Start Install as a Claude Code skill: Open any project and initialize the memory stack: At the end of a work session: Next time: For Cursor, Codex, and other assistants, see Tool Compatibility. Why It Exists AI coding assistants are powerful in one session and forgetful across sessions. If any of these sound familiar, pro
| Stars | 372 |
| Forks | 11 |
| Language | Shell |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 73.7641697392445/100 |
| Open Issues | 3 |
| Last Updated | 2026-07-29 |
| Created | 2026-04-21 |
| Platforms | claude-code, cli, codex |
| Est. Tokens | ~12k |
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project-butler is Project memory system for AI coding assistants (Claude Code, Cursor, Codex): session logs, project wiki, rules, TODOs, and handoff.. It is categorized as a Claude Skill with 372 GitHub stars.
project-butler is primarily written in Shell. It covers topics such as ai-agent, ai-coding, ai-workflow.
You can find installation instructions and usage details in the project-butler GitHub repository at github.com/JamesShi96/project-butler. The project has 372 stars and 11 forks, indicating an active community.
project-butler is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to project-butler on Agent Skills Hub include compose-skill, lerim, lerim-cli. 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: