by leo1oel · Codex Skill · ★ 228
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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 | 228 |
| Forks | 19 |
| Language | TypeScript |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 61/100 |
| Open Issues | 4 |
| Last Updated | 2026-11-07 |
| Created | 2026-07-16 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~16k |
Lattice A local-first LaTeX workspace for macOS, with your papers, your co-authors and an AI agent in the same window Download Try it in your browser Website Watch the film Release notes Developer docs Issues 中文 </
These tools work well together with lattice for enhanced workflows:
Looking for a lattice alternative? If you're comparing lattice 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.
Agent Skill that transforms AI assistants into expert economics paper writers. Synthesizes 50+ guides by Cochr
Manage MCP servers, skills and plugins across Claude Code, Codex, Cursor and more. Built-in marketplace, one-c
The AI agent that works while you don't watch. Lives in your menu bar, finds you when needed.
Run Codex inside Overleaf with a Chrome side panel, local LaTeX mirror, diff review, Track Changes support, un
Local-first macOS app to browse, search, analyze, and resume supported AI coding-agent session history across
Open-source cross-agent memory layer for coding agents via MCP. Compatible with Claude Code, Codex, Cursor, Wi
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: