What is an "AI skill" in this context?

An AI skill (here) means structured instructions—often Markdown or JSON—that tell an agent how to behave: templates, allowed tools, checklists, and domain-specific playbooks. It is not the model itself; it is the operating procedure the agent loads on top of the product defaults.

Is Agent Skill Manager only for Cursor?

No. The goal is portability across common AI development surfaces: Cursor-style rules, Claude-oriented setups, Copilot-adjacent flows—one install and audit path instead of a separate manual process per tool. Your stack may still use each product's native format; asm focuses on how you fetch, version, and review those instructions.

Why should I run asm audit before installing a skill?

Third-party skills can request file edits, shell commands, or network access. asm audit is the pre-flight check: you see what a skill is allowed to do before it runs, similar to reading package.json scripts or reviewing a shell installer. That matters most when you install from the open internet rather than an internal repo.

How is this different from copying .cursor rules between repos?

Copying folders does not give you a manifest, version pin, or permission summary per skill. A package-style flow (install → audit → run) makes team onboarding and security review repeatable. Copy-paste is fine for one repo; scale usually needs install and audit semantics.

How to manage AI skills across Claude, Cursor, and beyond

How to manage AI skills across Claude, Cursor, and other IDEs

Use one portable workflow instead of duplicating files: install skills from Git, audit permissions before you run them, and keep the same library whether you use Cursor rules, Claude Code definitions, or other agent surfaces. Agent Skill Manager (agent-skill-manager on npm, CLI asm) provides a terminal UI for that—list, install, and audit so capabilities travel with you, not as scattered markdown in hidden folders.

If you live in AI coding agents daily, the bottleneck is usually fragmentation, not model quality.

What is Agent Skill Manager (asm)?

Agent Skill Manager (asm) is an open-source CLI and TUI that treats agent instructions like installable packages: you can pull skills from repositories, inspect what a skill is allowed to do, and keep a single library across machines. It is published on npm as agent-skill-manager. The project positions itself as a bridge across tools (Cursor-style rules, Claude-oriented setups, Copilot-adjacent flows)—not a replacement for each vendor’s native format, but a shared layer on top.

Why skills get trapped in hidden directories

Most agents store capabilities locally—Cursor rules under project or user paths, Claude-specific definitions, ad hoc prompts. When you switch laptops, onboard a teammate, or try to standardize one workflow across Cursor, Claude, GitHub Copilot, and Windsurf, you often end up manually copying files between hidden directories. There was no shared package manager for how I talk to AI; that gap is what asm targets.

As a former FAANG engineer, I treat that fragmentation as a scaling tax: it works until it doesn’t, then it costs everyone time.

Manual copy-paste vs Agent Skill Manager

Approach	Portability	Audit before run	Install from a repo
Copy files by hand	Poor (drift between machines)	You verify manually	No standard path
asm	Designed around a shared library	`asm audit` surfaces permissions	`asm install github:user/repo`

Bottom line: If you only use one machine and one IDE, manual may be enough. If you care about repeatable installs and reviewing third-party skills before they touch your filesystem, asm matches that workflow.

How to install and run Agent Skill Manager

You need Node.js (or Bun) and npm.

Install globally: npm install -g agent-skill-manager
Launch the dashboard: run asm in your terminal
Review what’s installed: use the TUI to see current skills and what you can add next
Add a skill from GitHub: asm install github:user/repo (replace with the repo you trust)
Audit before you trust: run asm audit on third-party skills so you see what file, shell, or network access they expect—similar discipline to reviewing npm packages or shell scripts

What asm is optimized for

Centralized management — One TUI to view, install, and audit your skill library
Portability — Pull skills from a repo instead of hand-merging folders
Security-first workflow — asm audit before running unfamiliar skills with broad permissions
Cross-tool use — Same mental model whether the team leans on Claude, Cursor, Copilot, or a mix

Video walkthrough

The steps above align with the walkthrough in How to Manage AI Skills on YouTube (Master Your AI Agent Tool: Manage Skills Easily Across IDEs).

Building an AI-first developer stack

Managing skills is table stakes. As vibe coding and heavier agentic workflows spread, the edge goes to people who can orchestrate tools and instructions quickly—not to whoever has the longest .cursor folder on one machine.

Watch on YouTube: How to Manage AI Skills — or browse the rest of the channel at @DevsPlsFix.

Follow the build on DEVS PLS FIX as I ship open-source tools aimed at the rough edges of the modern dev workflow.