antigravity-awesome-skills and skills

Both projects offer collections of agentic skills, making them **competitors** in providing ready-to-use functionalities for AI agents.

skills
46
Emerging
Maintenance 25/25
Adoption 10/25
Maturity 11/25
Community 24/25
Maintenance 13/25
Adoption 9/25
Maturity 11/25
Community 13/25
Stars: 23,847
Forks: 4,099
Downloads:
Commits (30d): 533
Language: Python
License: MIT
Stars: 90
Forks: 11
Downloads:
Commits (30d): 0
Language: Python
License: MIT
No Package No Dependents
No Package No Dependents

About antigravity-awesome-skills

sickn33/antigravity-awesome-skills

The Ultimate Collection of 1000+ Agentic Skills for Claude Code/Antigravity/Cursor. Battle-tested, high-performance skills for AI agents including official skills from Anthropic and Vercel.

Provides an installable skill library distributed via CLI (`npx antigravity-awesome-skills`) that places reusable markdown playbooks into tool-specific directories for Claude Code, Cursor, Gemini CLI, and others. Organizes 1,331+ skills into curated bundles and multi-step workflows, separating operating instructions (skills) from external capabilities (MCP tools) to support planning, security, infrastructure, and product workflows. Integrates with major AI IDEs and agents through both direct installation paths and marketplace plugins, enabling natural invocation syntax like `@brainstorming` within agent conversations.

About skills

aahl/skills

AAHL's Agent Skills. 汇集了多种实用的智能体技能,涵盖Home Assistant智能家居控制、微软Edge TTS和智谱GLM-TTS文本转语音、DuckDuckGo搜索、DeepWiki文档检索、加密货币行情、天气预报、Lark/飞书、影视搜索、商品比价等功能

Implements modular agent skills via the MCP (Model Context Protocol) standard, enabling AI agents to execute specialized tasks through a plugin architecture installable via `npx skills add`. Features include voice I/O capabilities (Qwen ASR, Edge TTS, GLM-TTS), smart home automation through Home Assistant's MCP interface, and integrations with Chinese platforms (Lark/飞书, Xiaomi TV playback, price comparison across Taobao/JD.com/Pinduoduo). Skills are distributed as lightweight binaries with minimal dependencies, leveraging command-line tools (curl, jq, uv) rather than heavy SDKs.

Scores updated daily from GitHub, PyPI, and npm data. How scores work