Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
/plugin install insane-reviewTaken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 122 |
| Forks | 22 |
| Language | Python |
| Category | AI Tool |
| License | MIT |
| Quality Score | 70/100 |
| Open Issues | 6 |
| Last Updated | 2026-10-01 |
| Created | 2026-06-21 |
| Platforms | browser, claude-code, python |
| Est. Tokens | ~15k |
English Español insane-review GPT Pro (the Pro reasoning tier of the current flagship — currently GPT-5.6 Sol) has no API. This plugin uses it from inside Claude Code anyway. GPT Pro lives only in the ChatGPT web app (subscription) — there is no official API, so you can't reach it from Codex CLI, , or an agent-council API provider.
Looking for a insane-review alternative? If you're comparing insane-review with other ai tool tools, these 4 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
SciToolAgent: A Knowledge Graph-Driven Scientific Agent for Multi-Tool Integration
Skip to content github / docs Code Issues 80 Pull requests 35 Discussions Actions Projects 2 Security Insights
Skill to talk to Claude about your projects over the phone
.NET MAUI skills for GitHub Copilot and Claude Code
Explore other popular ai tool tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: