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Multi-harness agentic plugin marketplace for Claude Code, Codex, Cursor, OpenCode, GitHub Copilot, and Google Antigravity
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Production-ready agentic workflow building blocks: 94 plugins, 202 agents,
183 skills, 105 commands — built for Claude Code and consumed natively by
OpenAI Codex CLI, Cursor, OpenCode, the Antigravity CLI, GitHub Copilot, and Pi from a single Markdown source.
One source-of-truth (plugins/), six target harnesses. Each harness gets idiomatic,
harness-native artifacts — not lowest-common-denominator translations.
See docs/harnesses.md for the capability matrix.
→ Full Claude Code setup, troubleshooting, and plugin catalogRead the full README ↗
Use one collection of plugins, agents, skills, and commands across Claude Code, OpenAI Codex CLI, Cursor, OpenCode, Antigravity CLI, GitHub Copilot, and Pi. A harness is the coding tool that loads and runs the components.
Contributors write each component once, in Markdown, in the Claude Code plugin format. Adapters under tools/adapters/ generate the format each harness reads, map model aliases to that harness's models, and translate tool permissions where the harness supports them. CI regenerates the artifacts for every harness, validates them, and runs the OpenCode, Antigravity CLI, and Pi artifacts through their installed CLIs. The capability matrix lists what each harness supports, and ARCHITECTURE.md describes the design.
The catalog contains 94 plugins, including 92 local plugins and 2 external entries. The local source contains 202 agents, 185 skills, and 105 commands. Plugins cover Python and JavaScript development, code review, testing, infrastructure, security, and other work.
Choose the harness you use and follow its setup route. Available components depend on the installation route and the harness's capabilities.
| Tool | Installation | Components and limits |
|---|---|---|
| Claude Code | Plugin marketplace | Source agents, skills, and commands; plugin-specific hooks and MCP configuration |
| OpenAI Codex CLI | Native marketplace or generated artifacts | Native source skills; generated TOML agents and commands as skills use a separate route |
| Cursor | Plugin marketplace | Source agents, skills, and commands, with curated project rules |
| OpenCode | make install-opencode | Generated agents, skills, and commands, with translated tool permissions |
| Antigravity CLI | make install-antigravity | Generated plugins containing agents, skills, and commands |
| GitHub Copilot | make install-copilot | Generated agent profiles and skills; commands also become invocable skills |
| Pi | make install-pi | Generated skills and prompt templates; agents require a subagent extension |
See the capability matrix for model mappings, tool permissions, hooks, and installation differences.
For individual skills, use a skills-only installer and select your coding tool.
A plugin groups related agents, skills, and commands under plugins/. For example, python-development contains three agents, sixteen skills, and a scaffolding command. The chosen harness loads the installed components according to its own discovery and invocation rules.
Contributors maintain one Markdown source in the Claude Code plugin format. Native registries point to that source where supported, and adapters generate the formats needed by each harness. Commands may become skills or prompt templates, and agent formats, model choices, and tool permissions vary by harness.
Source agents specify model aliases such as opus, sonnet, haiku, fable, or inherit. Adapters map those aliases to each harness's model settings, including fixed defaults for some inherit entries. See model configuration and the adapter mappings.
The repository validates plugin structure, generated artifacts, and documentation. Contributors can run these checks from the repository root:
make generate-all
make validate STRICT=1
make garden
plugin-eval also provides static skill checks without model calls. For example:
uv run --project plugins/plugin-eval plugin-eval score plugins/python-development/skills/python-testing-patterns --depth quick
The LLM judge and Monte Carlo layers are experimental and are not validated against human labels. Their scores describe model assessments and repeated simulations and do not prove that a task succeeds in a project. They require the optional llm dependencies. Model calls use ANTHROPIC_API_KEY when it is set and bill that API account. Otherwise they use your Claude Code login. See the evaluation guide for setup and limits.
Choose a plugin for the work you do:
| Plugin | Use it for |
|---|---|
| python-development | Python, Django, FastAPI, testing, and packaging |
| javascript-typescript | JavaScript and TypeScript development and project setup |
| developer-essentials | Code review, debugging, Git, and testing patterns |
| security-scanning | Security review, dependency checks, and code scanning |
See the plugin catalog for all 94 plugins and the usage guide for commands and examples.
Run these commands inside Claude Code to register the marketplace and install the Python development plugin:
/plugin marketplace add wshobson/agents
/plugin install python-development@claude-code-workflows
Then ask Claude to use the Python agents for your task, or run the plugin's scaffolding command:
/python-development:python-scaffold Create a FastAPI service with tests
Run these commands in a terminal with a current Codex CLI:
codex plugin marketplace add wshobson/agents
codex plugin add python-development@claude-code-workflows
The native Codex manifests expose source skills. The generated TOML agents and command-derived skills use a separate adapter path. Native installation also reads the original skill bodies, while generated copies split oversized bodies into reference files for the 8 KB budget. See the Codex setup details before choosing an installation route.
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