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 microsoft · Codex Skill · ★ 3.9k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is apm safe to install? View the security audit →
APM – Agent Package Manager An open-source, community-driven dependency manager for AI agents. Think , , or — but for AI agent configuration. GitHub Copilot · Claude Code Documentation · Quick Start · CLI Reference Why APM AI coding agents need context to be useful — standards, prompts, skills, plugins — but today every developer sets this up manually. Nothing is portable nor reproducible. There's no manifest for it. APM fixes this. Declare your project's agentic dependencies once in , and every developer who clones your repo gets a fully configured agent setup in seconds — with transitive dependency resolution, just like npm or pip. Highlights One manifest for everything —
| Stars | 3,878 |
| Forks | 372 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 60.2926447113647/100 |
| Open Issues | 230 |
| Last Updated | 2026-09-22 |
| Created | 2025-09-18 |
| Platforms | claude-code, cli, codex, node, python, rust |
| Est. Tokens | ~14k |
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apm is Agent Package Manager. It is categorized as a Codex Skill with 3.9k GitHub stars.
apm is primarily written in Python. It covers topics such as ai-agents, claude-code, codex-cli.
You can find installation instructions and usage details in the apm GitHub repository at github.com/microsoft/apm. The project has 3.9k stars and 372 forks, indicating an active community.
apm is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to apm on Agent Skills Hub include quint-code, claude-scholar, ralph-orchestrator. 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: