Skill Cabinet

Agent Skills is a curated skill registry and npm-based CLI for extending AI coding agents such as Claude Code, Cursor, Copilot, and Antigravity with packaged instructions, templates, and reference files. The CLI fetches a catalog, lets users search and select skills, caches downloads locally, and installs them to selected agents by copying or symlinking them at global or project scope; it also supports updating, removing, auditing, and managing cached skills. The repository describes the catalog as an open-source, human-curated library with CI static analysis, content hashing, lockfiles, path isolation, symlink guards, sanitization, audit logging, and Snyk Agent Scan checks. It also includes an MCP server that exposes progressive-disclosure tools for listing, searching, reading, and fetching skill files. The CLI source is MIT-licensed; maintainer-authored skills are generally CC BY 4.0, while third-party skills retain their own licenses.

Skills is a command-line tool for the open agent skills ecosystem. It installs reusable instruction sets defined in SKILL.md files into supported coding agents such as OpenCode, Claude Code, Codex, Cursor, and others. The `npx skills` CLI resolves skills from GitHub, GitLab, other Git URLs, local paths, or direct file and archive URLs; lists available skills, selects individual skills, and installs them project-wide or globally by symlink or copy. It can also generate a prompt for a skill without installing it, launch a supported agent with that prompt, search for skills, update or remove installations, and create new SKILL.md templates. Skills use YAML frontmatter with a name and description, and the CLI discovers them in standard agent and repository skill directories. The project is licensed under the MIT License.

SkillRadar is open-source discovery, security, ranking, and routing infrastructure for Agent Skills and Codex. It discovers public SKILL.md files, parses their contents, performs conservative static checks for capabilities such as shell commands, dynamic execution, secret access, networking, package installation, filesystem writes, and deployment tooling, then classifies and ranks candidates in a safety-gated registry. D and Blocked candidates are kept audit-only and excluded from automatic routing. Its Codex plugin provides task-to-Top-3 routing, skill search, provenance and safety inspection, and a read-only Skill Budget Doctor. Routing can use a bundled offline registry and returns relevance, SkillRadar score, security grade, provenance, reasons, and match details without executing candidate repositories or depending on live GitHub discovery. The repository includes radar data, a matching system, a router-quality benchmark, a local registry UI, and daily bot-refreshed generated data; it is released under the MIT license.

Cangjie Skill is an open-source pipeline that distills methodologies from books, long-form videos, podcasts, interviews, and courses into callable AI Agent Skills rather than summaries. The resulting skills package evidence, examples, executable steps, and usage boundaries so coding agents can invoke the extracted methodology. Its capability-bundle workflow extracts stable capability cards and metadata before compiling installable output. It supports a single router-style Skill or a compact pack containing a router and promoted standalone Skills. The unified local toolchain includes diagnostics, compilation, output replanning, incremental updates, repair, rollback, evaluation, and benchmarking, while content-addressed preprocessing, source diffs, impact analysis, transactional patches, snapshots, and edit detection support controlled evolution. The repository also provides a standalone installation package for DeepSeek Harness.

self-learning-skills is a meta-skill for AI coding agents, including Claude Code, Cursor, Codex, and agents that read AGENTS.md or similar standing-instruction files. It recognizes hard-won, reusable procedures such as non-obvious commands and recurring operational workflows, then captures them as skills, rules, or project instructions for later sessions. The capture includes known dead ends and excludes one-off details and secret values. The project stores learned procedures as new skills/<name>/SKILL.md files for Claude Code, Codex, and Agent Skills clients; as .cursor/rules/learned/<name>.mdc files for Cursor; or in AGENTS.md or project notes for other agents. It can be installed with the community skills CLI, as a Claude Code plugin, or manually by copying the relevant files.