razbakov

Skill Mix — AI skill for Claude Code

AI community

A management layer for AI agent skills — discover, install, scope, rate, and update skills across Cursor, Codex, and Claude Code.

How to install Skill Mix

This entry records only its repository, not the path inside it, so there is no exact command to give. Open razbakov/skill-mix and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Skill Mix does

A management layer for AI agent skills — discover, install, scope, rate, and update skills across Cursor, Codex, and Claude Code.

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README

Skill Mix

A management layer for AI agent skills — discover, install, scope, rate, and update skills across Cursor, Codex, and Claude Code.

All three tools follow the open [Agent Skills](https://agentskills.io/) standard (`SKILL.md`), but none solves the management problem: how to find the right skill, avoid duplicates, track where it came from, or know if it's any good.

Setup

Quick install Skill Mix, open the app, and launch the skill-picker modal:

npx -y skill-mix obra/superpowers

Classic installer:

curl -fsSL https://raw.githubusercontent.com/razbakov/skills-manager/main/scripts/install.sh | bash

Usage

Run `skills` to launch application

Open/focus the app and trigger the skill-picker from CLI:

![Skill Mix desktop UI](docs/images/desktop-ui.png)

Build DMG (macOS)

bun install
bun run dist:dmg

This outputs a DMG installer in `release/`.

Problem

See **[Research](docs/research.md)** for how tools handle skills today, **[User Problems](docs/problems.md)** for 14 documented pain points, **[Landscape](docs/landscape.md)** for existing directories and tools, and **[Competitors](docs/competitors.md)** for detailed analysis of current solutions and their gaps.

Naming collisions — Multiple skills share similar names or overlap in responsibility. Cursor has no detection; Codex shows both without merging; Claude Code overrides by scope precedence.
No development workflow — No way to test, enable, or disable skills without editing files by hand (Codex has config.toml, but no UI).
Unknown provenance — None of the three tools track where a skill came from, who wrote it, or how to update it.
Scattered collections — Skills live in 3–6 different directories per tool with no unified view.
No quality signals — No ratings, benchmarks, or reviews exist anywhere in the ecosystem.