by mode-io
Manage skills across Codex CLI, Claude Code, Cursor, OpenCode, and OpenClaw from one local app.
# Add to your Claude Code skills
git clone https://github.com/mode-io/skill-managerGuides for using ai agents skills like skill-manager.
Last scanned: 5/30/2026
{
"issues": [
{
"type": "npm-audit",
"message": "picomatch: Picomatch: Method Injection in POSIX Character Classes causes incorrect Glob Matching",
"severity": "high"
},
{
"type": "npm-audit",
"message": "postcss: PostCSS has XSS via Unescaped </style> in its CSS Stringify Output",
"severity": "medium"
},
{
"type": "npm-audit",
"message": "vite: Vite Vulnerable to Path Traversal in Optimized Deps `.map` Handling",
"severity": "high"
},
{
"type": "npm-audit",
"message": "ws: ws: Uninitialized memory disclosure",
"severity": "medium"
}
],
"status": "WARNING",
"scannedAt": "2026-05-30T16:14:24.443Z",
"npmAuditRan": true,
"pipAuditRan": false
}See how skill-manager compares with popular alternatives.
skill-manager is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by mode-io. Manage skills across Codex CLI, Claude Code, Cursor, OpenCode, and OpenClaw from one local app. It has 121 GitHub stars.
skill-manager returned warnings in SkillsLLM's automated security scan. It has no critical vulnerabilities, but review the flagged issues in the Security Report section before adding it to your workflow.
Clone the repository with "git clone https://github.com/mode-io/skill-manager" and add it to your Claude Code skills directory (see the Installation section above).
skill-manager is primarily written in TypeScript. It is open-source under mode-io on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh skill-manager against similar tools.
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Requires a passing catalog security scan. Resolve the flagged issues and resubmit to enable featuring.
⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
AI extensions are scattered across harness-specific folders, MCP config files, slash command locations, and marketplace sources. Skill Manager gives those pieces one local control surface:
| Product idea | What it means |
|---|---|
| In use | Skill Manager controls the item and can enable or disable it across harnesses. |
| Needs review | Skill Manager found local state, config differences, or inventory issues that need a decision. |
| Scan | Run LLM-backed security checks against Skills before trusting them. |
| Discover | Browse marketplaces and preview external tools. |
Start with the whole extension portfolio: what is in use, what needs review, what can be discovered, and where extensions are active.

Use Skills as shared local packages instead of maintaining separate copies per harness.
Typical flow:

Scan Skills with an LLM-backed security review before you rely on them.
Typical flow:
Scan configurations are managed separately so you can save multiple providers, choose one active configuration, and keep API keys masked in list views.
Use MCP servers as one normalized config that can be written into each harness shape.
Typical flow:

Use slash commands as one shared prompt library instead of rewriting the same command in each harness-specific format.
Typical flow:
$ARGUMENTS where runtime input should be inserted.
Marketplace is the discovery surface:

brew tap mode-io/tap
brew install skill-manager
skill-manager start
npm install -g @mode-io/skill-manager
skill-manager start
The npm wrapper downloads the native release artifact for the current platform and CPU architecture. Native release artifacts are published on GitHub Releases for macOS ARM64/x64, Linux x64/ARM64, and Windows x64.
Native Windows support targets Windows 10 22H2 and Windows 11 on x64 local disks. It does not require WSL, administrator privileges, or Windows Developer Mode.
The first Windows release supports the complete Codex CLI + Skills flow: discover an existing Codex CLI installation, install or adopt Skills, and enable or disable them under %USERPROFILE%\.agents\skills. Skill Manager does not install, update, or sign in to Codex. Other harnesses, MCP server management, and slash command management are not yet supported on Windows.
Windows ARM64, Windows Server, UNC paths, mapped network drives, and removable drives are outside the current support scope.
| Harness | Skills | MCP servers | Slash commands |
|---|---|---|---|
| Codex CLI | Yes | Yes | Yes |
| Claude Code | Yes | Yes | Yes |
| Cursor | Yes | Yes | Yes |
| OpenCode | Yes | Yes | Yes |
| Hermes Agent | Yes | Yes | Not Yet |
| OpenClaw | Yes | Not Yet | Not Yet |
The table above describes macOS/Linux support. The initial native Windows support matrix is:
| Harness | Skills | MCP servers | Slash commands |
|---|---|---|---|
| Codex CLI | Yes | Not Yet | Not Yet |
| Other harnesses | Not Yet | Not Yet | Not Yet |
Skill Manager is a local configuration-management tool. It runs on your machine and reads or writes local harness extension state.
Actions that can change local state include:
App-owned files live under ~/Library/Application Support/skill-manager on macOS, XDG base directories on Linux, and %APPDATA%\skill-manager plus %LOCALAPPDATA%\skill-manager on Windows.
Before adoption, each harness points at its own local skill folder. After adoption, Skill Manager keeps one canonical package in its shared local store and exposes it to selected harnesses with local links. It uses symbolic links on macOS/Linux and ordinary-user directory junctions on Windows. Disabling a harness removes that harness binding without deleting the package.
Skill Manager treats managed Skills as portable by default: once a Skill is adopted into the shared store, it can be enabled for any supported harness. originHarness is retained only as p