By discopops
Your AI development teammate. Turns a story file into a shipped, reviewed, and tested feature via orchestrator → architect → developer → PR reviewer → QA → Playwright.
Initialises the ShipMate pipeline in the current project. Creates the stories folder, sets up the pipeline state directory, and runs the initial codebase scan to generate project-doc.md and AGENTS.md.
Master pipeline entry point. Routes requirements from a story file through scan → orchestrate → architect → implement → review → QA → playwright stages. Use /ship stories/foo.md to start, /ship status to check progress, /ship resume to continue.
Architect agent. Reads orchestrator-output.md, AGENTS.md, and project-doc.md to produce a numbered step-by-step implementation plan. Pauses for human approval before implementation begins.
Developer agent. Implements the architect plan step-by-step, guided by AGENTS.md guardrails. Writes tests, leaves no TODOs, and flags plan deviations rather than silently skipping them.
Product Orchestrator agent. Reads the active story file, asks clarifying product questions one at a time, confirms task type (FRONTEND/BACKEND), and produces a complete unambiguous spec in orchestrator-output.md.
Playwright testing agent. Only runs for FRONTEND tasks. Verifies acceptance criteria in a real browser using the page object pattern. Passes on success, routes back to developer on failure.
QA Agent. Tests all acceptance criteria and edge cases from orchestrator-output.md. Generates a structured qa-report.md with pass/fail per criterion and bug triage. Loops back to implement if bugs found (max 2 iterations).
Uses power tools
Uses Bash, Write, or Edit tools
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Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Production-ready agentic workflow building blocks: 82 plugins, 191 agents, 155 skills, 102 commands — built for Claude Code and consumed natively by OpenAI Codex CLI, Cursor, OpenCode, and Gemini CLI 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.
Pick your harness:
/plugin marketplace add wshobson/agents
/plugin install python-development # or any of 82 plugins
→ Full Claude Code setup, troubleshooting, and plugin catalog
gh repo clone wshobson/agents ~/agents
cd ~/agents
make generate HARNESS=<codex|cursor|opencode|gemini>
Per-harness setup guides: CODEX.md · CURSOR.md · OPENCODE.md · GEMINI.md
| Count | What it is | |
|---|---|---|
| Plugins | 82 | Granular, single-purpose installable units (81 local + 1 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
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 |
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 | .codex/skills/, .codex/agents/, AGENTS.md | 8 KB skill cap respected; commands → skills |
| Cursor | .cursor-plugin/, .cursor/rules/ | Thin marketplace + curated rules; reuses .claude/ |
| OpenCode | .opencode/agents/, .opencode/commands/ | permission: block from tools: allowlist |
| Gemini CLI | skills/, agents/, commands/ (TOML) | Native skills + subagents (April 2026 spec) |
make generate-all # all four
make validate # structural checks
make garden # drift / dead-link / cap detection
→ Full capability matrix and per-harness deep-dives
plugin-eval is a three-layer evaluation framework for measuring
and certifying plugin/skill quality:
uv run plugin-eval score path/to/skill --depth quick
uv run plugin-eval certify path/to/skill
→ PluginEval framework documentation
Detail lives in docs/. Read in this order:
npx claudepluginhub p/discopops-ship-mate-plugins-ship-mateMulti-perspective code analysis covering architecture, security, and best practices
Pre-deployment checks, configuration validation, and deployment readiness assessment
Database architecture, schema design, and SQL optimization for production systems
Deployment patterns, rollback automation, and infrastructure templates
Distributed system tracing and debugging across microservices
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.
Harness-native ECC plugin for engineering teams - 67 agents, 278 skills, 94 legacy command shims, reusable hooks, rules, MCP conventions, and operator workflows for Claude Code plus adjacent agent harnesses
Tools to maintain and improve CLAUDE.md files - audit quality, capture session learnings, and keep project memory current.
Consult multiple AI coding agents (Gemini, OpenAI, Grok, Perplexity, plus codex, antigravity, and grok CLIs when installed) to get diverse perspectives on coding problems
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
Matt Pocock's agent skills for real engineering — grilling, spec/ticket flows, TDD, code review, domain modelling and more. Plug-and-play, not vibe coding.