by BichengWang · Codex Skill · ★ 95
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. 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 | 95 |
| Forks | 9 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 67/100 |
| Last Updated | 2026-10-21 |
| Created | 2025-04-21 |
| Platforms | claude-code, codex, python |
| Est. Tokens | ~14k |
multi-agents Multi-agent teams for real work: measured, not assumed. Run a team of coding agents on a task in your repository: a single agent, a coder ⇄ reviewer loop, or several agents with a judge. Workers are the coding CLIs you already use (Claude Code, Codex) or a built-in agent that can use any model through the OpenAI Agents SDK. Each worker gets its own git worktree.
These tools work well together with multi-agents for enhanced workflows:
Looking for a multi-agents alternative? If you're comparing multi-agents 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.
Reusable project context and specialist workflows for the AI tools you already use. Agents, skills, rules and
Governance-first orchestration for Claude Code, Codex, and Gemini CLI — parallel workers, receipts, quality ga
The ADE for AI agents. Automate everything else. Do your true work.
The World's First Agentic IDE. Visual dashboard: live sessions, task management, code editor, terminal. Epic S
The rules layer for AI-written code — rig-lite: a fail-closed cross-model review gate, a written constitution,
An LLM council that reviews your coding agent's every move
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: