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 w1ckedxt · MCP Server · ★ 97
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is cynical-sally safe to install? View the security audit →
Cynical Sally Brutally honest code reviews. In your terminal and your AI editor. Because "You're absolutely right" is probably absolutely wrong. npm i -g @cynicalsally/cli · MCP server for Claude Code, Cursor & Windsurf <a href="https://gi
| Stars | 97 |
| Forks | 9 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 70.430702908725/100 |
| Open Issues | 1 |
| Last Updated | 2026-07-04 |
| Created | 2026-02-27 |
| Platforms | claude-code, cli, mcp, node |
| Est. Tokens | ~17k |
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cynical-sally is Brutally honest senior-engineer code reviews for Claude Code, Cursor & Windsurf - and your terminal. Scores, evidence-backed issues, usable fixes.. It is categorized as a MCP Server with 97 GitHub stars.
cynical-sally is primarily written in TypeScript. It covers topics such as ai, ai-code-review, claude.
You can find installation instructions and usage details in the cynical-sally GitHub repository at github.com/w1ckedxt/cynical-sally. The project has 97 stars and 9 forks, indicating an active community.
cynical-sally is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to cynical-sally on Agent Skills Hub include agnix, claude-historian-mcp, ollama-mcp. 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: