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 MrZoyo · Claude Skill · ★ 83
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is deslop-GPT safe to install? View the security audit →
deslop A deletion-first Agent Skill for agent-maintained codebases 简体中文 · English Evidence-backed cleanup that reduces accumulated machinery while preserving real behavior. audits and, when explicitly authorized, removes complexity accumulated through repeated coding-agent implement
| Stars | 83 |
| Forks | 0 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 65.4405551007408/100 |
| Last Updated | 2026-09-04 |
| Created | 2026-08-24 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~17k |
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deslop-GPT is Deletion-first Agent Skill for removing test bloat, verification theater, and speculative fallbacks while preserving behavior.. It is categorized as a Claude Skill with 83 GitHub stars.
deslop-GPT is primarily written in Python. It covers topics such as agent-skills, claude, claude-ai.
You can find installation instructions and usage details in the deslop-GPT GitHub repository at github.com/MrZoyo/deslop-GPT. The project has 83 stars and 0 forks, indicating an active community.
deslop-GPT is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to deslop-GPT on Agent Skills Hub include claudepro-directory, ask-user-questions-mcp, tutor-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: