#other #agent_skills #ai_agents #antigravity_skills #awesome #awesome_list #awesome_lists #claude_code #claude_code_skills #claude_skills #codex_skills #cursor_skills #gemini_skills #opencode_skills #skills

This curated collection offers over 1100 hand-picked Agent Skills from top teams like Anthropic, Google, Vercel, Stripe, Cloudflare, Microsoft, OpenAI, and Figma, plus community gems for coding, security, marketing, and more—compatible with Claude Code, Codex, Cursor, and others. Unlike AI-generated junk, these are real-world tools for tasks like document editing, cloud deployments, auth setups, and PM workflows. You'll save hours debugging, boost code quality, and ship faster with expert guidance directly in your AI tools.

https://github.com/VoltAgent/awesome-agent-skills

#javascript #claude #codex #marketing

Marketing Skills for AI Agents offers markdown files with specialized workflows for AI agents to handle tasks like SEO audits, copywriting, CRO, paid ads, analytics, and growth strategies. All skills build on a core product-marketing-context file and cross-reference each other for better results. Install easily via CLI (e.g., `npx skills add coreyhaines31/marketingskills`), Claude Code, or git, then ask your agent to optimize pages or write emails—it works with Claude, Cursor, and more under a permissive MIT license. This saves you time on marketing, boosts conversions and growth using proven best practices.

https://github.com/coreyhaines31/marketingskills

#typescript #antigravity #claude #claude_code #claude_code_hooks #claude_code_plugins #claude_code_skill #codex #codex_cli #context_mode #copilot #cursor_plugin #kiro #mcp #mcp_server #mcp_tools #openclaw #opencode #pi_agent #skills #zed_extension

Context Mode is an MCP server that fixes context window overload in AI coding tools by sandboxing raw data (like 56KB snapshots or logs) outside chats—shrinking 315KB to 5.4KB (98% savings), tracking sessions in SQLite for seamless resumes after compaction, and making LLMs generate code for analysis instead of dumping data. It installs easily on 12 platforms (Claude Code, Cursor, etc.) with hooks for auto-routing. You benefit by extending sessions 6x longer, picking up tasks instantly without re-explaining, and boosting productivity on big repos or logs.

https://github.com/mksglu/context-mode

#go #api #claude_api #deepseek #deepseek_api #docker #freeapi #go #openai_api #proxy #proxy_server #react #vercel #vercel_deployment #zeabur

DS2API turns DeepSeek web chat into APIs compatible with OpenAI, Claude, and Gemini, using Go backend and React web UI for easy management. It supports multi-account rotation, concurrency queues, tool calling, and models like deepseek-chat/reasoner with aliases (e.g., gpt-5). Deploy simply via release binaries, Docker, Vercel, or source—edit config.json with your keys/accounts and run. You benefit by accessing DeepSeek affordably through familiar SDKs, saving costs and simplifying integration for apps or testing.

https://github.com/CJackHwang/ds2api

#go #agents #claude_code #coding

Beads (bd) is a free CLI tool for macOS, Linux, Windows, and FreeBSD that gives AI coding agents persistent, structured memory via a version-controlled Dolt SQL database with graphs for tasks, dependencies, and hierarchies. Install once with `curl` script or brew, then `bd init` in any project—no repo cloning needed. Key commands like `bd ready`, `bd create`, and `bd update` track blockers, claim tasks, and auto-detect ready work in JSON for agents. It prevents conflicts with hash IDs, compacts old tasks, and supports stealth/git-free modes. You benefit by replacing messy plans with clear, long-term task tracking that keeps AI agents focused without losing context, boosting productivity on complex projects.

https://github.com/gastownhall/beads

#rust #ai #claude #cli #coding_agent #llm #mcp #openai #rust #terminal #tui

jcode is a fast, low-RAM coding agent for Linux, macOS, and Windows that boosts your skills with multi-session workflows, smart memory recall, swarm collaboration, side panels for diagrams/files, and logins for models like Claude or OpenAI. Install easily via `curl -fsSL https://raw.githubusercontent.com/1jehuang/jcode/master/scripts/install.sh | bash`, then run `jcode`. It uses far less memory (27MB vs. 300MB+ for rivals) and starts in 14ms, letting you handle many agents smoothly without slowdowns or high costs—perfect for efficient, scalable coding.

https://github.com/1jehuang/jcode

#shell #agent_skills #antigravity #antigravity_ide #claude_code #cursor #skills

Agent Skills gives AI coding agents structured workflows that follow how senior engineers build software. You get 20 skills organized across six development phases—Define, Plan, Build, Verify, Review, and Ship—each with step-by-step processes, quality gates, and verification requirements. Seven slash commands activate the right skills automatically based on what you're doing. This benefits you by ensuring AI agents consistently follow production-grade practices like writing specs before code, testing thoroughly, reviewing for quality, and deploying safely. Instead of taking shortcuts, your AI assistant now enforces the same discipline that makes reliable software, whether you're using Claude, Cursor, Gemini, or other coding tools.

https://github.com/addyosmani/agent-skills

#javascript #ai_agents #ai_gateway #anthropic #chatgpt #claude #claude_code #cline #codex #copilot #cursor #deepseek #free_ai #gemini #gemini_cli #llm #llm_gateway #openai #openai_proxy #qwen #token_saver

# 9Router//localhost:20128/v1`. You get unlimited coding with zero cost, no downtime, and intelligent fallback routing—perfect for developers who want maximum value from AI without subscription limits or surprise bills.

https://github.com/decolua/9router

#typescript #agentmemory #agents #ai #claude #claudecode #codex #copilot #cursor #genai #harness #hermes #memory #openclaw

# agentmemory `npx @agentmemory/agentmemory`.

https://github.com/rohitg00/agentmemory

#python #academic_pipeline #academic_writing #ai_research #claude #claude_code #literature_review #peer_review #prompt_engineering

# Academic Research Skills for Claude Code

This is a comprehensive toolkit that helps you write research papers from start to finish. Instead of AI writing your paper alone, it works as your research partner—handling the tedious work like finding sources, checking citations, and organizing arguments, while you focus on the thinking and writing that only you can do.

The system includes four main tools: Deep Research (for finding and organizing information), Academic Paper (for writing), Academic Paper Reviewer (for getting feedback), and Academic Pipeline (which coordinates everything together). You can use individual tools or run the complete pipeline. It supports multiple languages, citation formats, and paper types. The toolkit emphasizes human control at every step—you make the final decisions, and the AI flags potential problems like hallucinated references or weak arguments. Installation takes 30 seconds via plugin marketplace, and it costs roughly $4–6 to write a complete 15,000-word paper.

https://github.com/Imbad0202/academic-research-skills