Agentic Plugin Marketplace

Production-ready agentic workflow building blocks: 83 plugins, 191 agents,
155 skills, 102 commands — built for Claude Code and consumed natively by
OpenAI Codex CLI, Cursor, OpenCode, Gemini CLI, and GitHub Copilot from a single Markdown source.

[!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

bash
/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

Codex and Cursor install natively from the committed registries (which point at the source plugins/):

bash
npx codex-marketplace add wshobson/agents        # Codex; then install individual plugins
# Cursor: add the marketplace, then `/plugin install <name>` (reads .cursor-plugin/ + source)

Gemini and OpenCode install via clone + generate (the transformed trees are gitignored):

bash
gh repo clone wshobson/agents ~/agents && cd ~/agents
make generate HARNESS=gemini && gemini extensions install .   # Gemini
make install-opencode                                          # OpenCode (runs generate + symlinks)

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

What's inside

	Count	What it is
Plugins	83	Granular, single-purpose installable units (81 local + 2 external via git-subdir)
Agents	191	Domain experts (architecture, languages, infra, security, data, ML, docs, business, SEO)
Skills	155	Modular knowledge packages with progressive disclosure (load when activated)
Commands	102	Slash commands: scaffolding, security scans, test gen, infrastructure setup
Orchestrators	16	Multi-agent coordination workflows (full-stack, security, ML, incident response)

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:

Tier	Model	Use
1	Opus 4.7	Architecture, security, code review, production-critical
2	inherit	User-chosen — backend, frontend, AI/ML, specialized
3	Sonnet	Docs, testing, debugging, API references
4	Haiku	Fast operational tasks, SEO, deployment, content

→ 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):

Harness	Generates	Notes
Claude Code	(source-of-truth)	Native `marketplace.json` + `plugins/`
Codex CLI	`.agents/plugins/marketplace.json` + `plugins/*/.codex-plugin/plugin.json` (committed); `.codex/skills/`, `.codex/agents/` (gitignored)	8 KB skill cap respected; commands → skills
Cursor	`.cursor-plugin/`, `.cursor/rules/`	Thin marketplace + curated rules; reuses `.claude/`
OpenCode	`.opencode/agents/`, `.opencode/commands/`, `.opencode/skills/`	`permission:` block from `tools:` allowlist; OpenCode-safe skill names
Gemini CLI	`skills/`, `agents/`, `commands/` (TOML)	Native skills + subagents (April 2026 spec)
Copilot	`.copilot/agents/`, `.copilot/skills/`, `.copilot/commands/`	Markdown agent profiles + SKILL.md skills + commands-as-skills; model maps to GPT-5 family

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

Codex and Cursor install from source via committed registries; Gemini and OpenCode install via clone + make.

→ 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)

bash
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.

Harness	Pensyve integration
Claude Code	`/plugin install pensyve` from this marketplace (`integrations/claude-code`)
Codex CLI	integrations/codex-plugin
Cursor	integrations/cursor
OpenCode	integrations/opencode-plugin
Gemini CLI	`gemini extensions install https://github.com/major7apps/pensyve`
Copilot	`.copilot/` in repo root or `~/.copilot/` via `make install-copilot`