by appautomaton · MCP Server · ★ 120
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Language: English | 中文 Agent Designer A portable skills workspace for AI coding agents — Codex, Claude Code, and Gemini. Design structured, reusable skills that give your agents clear workflows, safe defaults, and multi-turn collaboration capabilities. Clone this repo as a starting point for any project where you want agents to work methodically rather than freestyle. What's inside Collaboration skills — let your agents delegate to each other via bridge scripts with session continuity: Issue-driven development — structure work into plans and trackable Issue CSVs: Getting started [!TIP] 1) (Optional) Use this repo as a template: clone it, remove git history (), re-init (). 2) Write your — project role, constraints, stack, safety rules. - To add issue-driven workflow: ask your agent to "apply on top of ". 3) Start working — ask your agent to create a plan, generate an Issue CSV, or collaborate with another agent. - Example:
| Stars | 120 |
| Forks | 17 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 47.816/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-16 |
| Created | 2025-12-20 |
| Platforms | claude-code, cli, codex, gemini, mcp, python |
| Est. Tokens | ~11k |
These tools work well together with agent-designer for enhanced workflows:
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agent-designer is Portable SKILLs workspace for Claude Code, Codex, and Gemini — issue-driven workflows and cross-agent collaboration via bridge scripts with session continuity.. It is categorized as a MCP Server with 120 GitHub stars.
agent-designer is primarily written in Python. It covers topics such as agent-skills, agentic-workflows, ai-agents.
You can find installation instructions and usage details in the agent-designer GitHub repository at github.com/appautomaton/agent-designer. The project has 120 stars and 17 forks, indicating an active community.
The top alternatives to agent-designer on Agent Skills Hub include agent-skills, memorix, claude-elixir-phoenix. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.