by usetig · Codex Skill · ★ 106
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
npm install -g @tigtech/sageTaken from the project's README on GitHub.
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.
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 | 106 |
| Forks | 8 |
| Language | TypeScript |
| Category | Codex Skill |
| Quality Score | 63/100 |
| Open Issues | 5 |
| Last Updated | 2026-04-28 |
| Created | 2025-10-24 |
| Platforms | claude-code, cli, codex, gemini, node |
| Est. Tokens | ~485k |
Sage Sage is like a senior engineer that watches your coding agent's every move. Unlike existing review tools, Sage doesn't just look at code — it critiques your agent's responses, reasoning, and plans so you can catch issues before they're implemented.
These tools work well together with sage for enhanced workflows:
Looking for a sage alternative? If you're comparing sage with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
🐑 One command to configure all AI coding tools — Claude Code, Codex, Gemini CLI, Cursor, Aider & more
A collection of AI agent skills for Clawdbot, Claude Code, Codex
Reusable project context and specialist workflows for the AI tools you already use. Agents, skills, rules and
The rules layer for AI-written code — rig-lite: a fail-closed cross-model review gate, a written constitution,
Let Claude Code and other coding agents drive and debug Chrome from the shell. DOM, network, console and raw C
The Universal AI-Optimized Project Boilerplate. A Tiered Memory System (TMS) designed to maximize AI agent per
Explore other popular codex skill 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: