One-line summary from the repository description on GitHub

Adopt with confidence

[!NOTE] One source-of-truth (plugins/), five harnesses. Each harness gets idiomatic, harness-native artifacts — not lowest-common-denominator translations. See docs/harnesses.md for the capability matrix.

Quick start

Pick your harness:

Claude Code

/plugin marketplace add wshobson/agents
/plugin install python-development          # or any of 83 plugins

→ Full Claude Code setup, troubleshooting, and plugin catalog

Codex CLI · Cursor · OpenCode · Gemini CLI · Copilot

gh repo clone wshobson/agents ~/agents
cd ~/agents
make generate HARNESS=<codex|cursor|opencode|gemini|copilot>

Setup details and per-harness gotchas: docs/harnesses.md. Gemini-specific setup: GEMINI.md (also auto-loaded by Gemini CLI).

What's inside

Browse the catalog: docs/plugins.md · docs/agents.md · docs/agent-skills.md

How it works

Each plugin is isolated and composable: agents, commands, and skills are auto-discovered from directory structure. Installing a plugin loads only its components into context — not the whole marketplace.

plugins/python-development/
├── .claude-plugin/plugin.json
├── agents/             # 3 Python agents (python-pro, django-pro, fastapi-pro)
├── commands/           # 1 scaffolding command
└── skills/             # 16 specialized skills (async, testing, packaging, …)

Three-tier model strategy:

→ Model configuration details

Multi-harness support

This marketplace ships to five agentic harnesses from one Markdown source. Each adapter emits harness-native artifacts (not lowest-common-denominator translations):

make generate-all                        # all five
make validate                            # structural checks
make garden                              # drift / dead-link / cap detection

→ Full capability matrix and per-harness deep-dives

Quality evaluation

plugin-eval is a three-layer evaluation framework for measuring and certifying plugin/skill quality:

• Static — deterministic structural analysis (<2s, free)
• LLM Judge — semantic evaluation across 4 dimensions (~30s, Haiku + Sonnet)
• Monte Carlo — statistical reliability via 50-100 simulated runs (~2-5 min)

uv run plugin-eval score path/to/skill --depth quick
uv run plugin-eval certify path/to/skill

→ PluginEval framework documentation

Documentation map

Detail lives in docs/. Read in this order:

• docs/plugins.md — full catalog of all 83 plugins
• docs/agents.md — all 191 agents by category
• docs/agent-skills.md — 155 skills with progressive disclosure
• docs/usage.md — commands, workflows, examples
• docs/architecture.md — design principles
• docs/harnesses.md — cross-harness capability matrix
• docs/authoring.md — portable-content style guide
• docs/plugin-eval.md — quality evaluation framework
• docs/round-trip-results.md — real-CLI verification recipes

Gemini-specific setup: GEMINI.md. All other harness setup, capability deltas, and gotchas live in docs/harnesses.md.

Contributing: CONTRIBUTING.md · Authoring: docs/authoring.md

External Memory Integration

Pensyve is included as an external git-subdir entry for Claude Code. Pensyve also maintains direct upstream integrations for this marketplace's other supported harnesses.

License

MIT — see LICENSE.

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