create-cowork-plugin
Create Cowork Plugin guides users through a five-phase conversational workflow to build a custom Claude plugin from scratch. The skill handles discovery of plugin requirements, planning of necessary components like skills and agents, detailed design specification, implementation of all plugin files, and final packaging into a ready-to-install `.plugin` file, maintaining nontechnical language throughout while encoding the full plugin architecture and directory structure standards.
git clone --depth 1 https://github.com/openyak/openyak /tmp/create-cowork-plugin && cp -r /tmp/create-cowork-plugin/backend/app/data/plugins/cowork-plugin-management/skills/create-cowork-plugin ~/.claude/skills/create-cowork-pluginSKILL.md
# Create Cowork Plugin
Build a new plugin from scratch through guided conversation. Walk the user through discovery, planning, design, implementation, and packaging — delivering a ready-to-install `.plugin` file at the end.
## Overview
A plugin is a self-contained directory that extends Claude's capabilities with skills, agents, hooks, and MCP server integrations. This skill encodes the full plugin architecture and a five-phase workflow for creating one conversationally.
The process:
1. **Discovery** — understand what the user wants to build
2. **Component Planning** — determine which component types are needed
3. **Design & Clarifying Questions** — specify each component in detail
4. **Implementation** — create all plugin files
5. **Review & Package** — deliver the `.plugin` file
> **Nontechnical output**: Keep all user-facing conversation in plain language. Do not expose implementation details like file paths, directory structures, or schema fields unless the user asks. Frame everything in terms of what the plugin will do.
## Plugin Architecture
### Directory Structure
Every plugin follows this layout:
```
plugin-name/
├── .claude-plugin/
│ └── plugin.json # Required: plugin manifest
├── skills/ # Skills (subdirectories with SKILL.md)
│ └── skill-name/
│ ├── SKILL.md
│ └── references/
├── agents/ # Subagent definitions (.md files)
├── .mcp.json # MCP server definitions
└── README.md # Plugin documentation
```
> **Legacy `commands/` format**: Older plugins may include a `commands/` directory with single-file `.md` slash commands. This format still works, but new plugins should use `skills/*/SKILL.md` instead — the Cowork UI presents both as a single "Skills" concept, and the skills format supports progressive disclosure via `references/`.
**Rules:**
- `.claude-plugin/plugin.json` is always required
- Component directories (`skills/`, `agents/`) go at the plugin root, not inside `.claude-plugin/`
- Only create directories for components the plugin actually uses
- Use kebab-case for all directory and file names
### plugin.json Manifest
Located at `.claude-plugin/plugin.json`. Minimal required field is `name`.
```json
{
"name": "plugin-name",
"version": "0.1.0",
"description": "Brief explanation of plugin purpose",
"author": {
"name": "Author Name"
}
}
```
**Name rules:** kebab-case, lowercase with hyphens, no spaces or special characters.
**Version:** semver format (MAJOR.MINOR.PATCH). Start at `0.1.0`.
Optional fields: `homepage`, `repository`, `license`, `keywords`.
Custom component paths can be specified (supplements, does not replace, auto-discovery):
```json
{
"commands": "./custom-commands",
"agents": ["./agents", "./specialized-agents"],
"hooks": "./config/hooks.json",
"mcpServers": "./.mcp.json"
}
```
### Component Schemas
Detailed schemas for each component type are in `references/component-schemas.md`. Summary:
| Component | Location | Format |
| ---------------------------------- | ------------------- | --------------------------- |
| Skills | `skills/*/SKILL.md` | Markdown + YAML frontmatter |
| MCP Servers | `.mcp.json` | JSON |
| Agents (uncommonly used in Cowork) | `agents/*.md` | Markdown + YAML frontmatter |
| Hooks (rarely used in Cowork) | `hooks/hooks.json` | JSON |
| Commands (legacy) | `commands/*.md` | Markdown + YAML frontmatter |
This schema is shared with Claude Code's plugin system, but you're creating a plugin for Claude Cowork, a desktop app for doing knowledge work.
Cowork users will usually find skills the most useful. **Scaffold new plugins with `skills/*/SKILL.md` — do not create `commands/` unless the user explicitly needs the legacy single-file format.**
### Customizable plugins with `~~` placeholders
> **Do not use or ask about this pattern by default.** Only introduce `~~` placeholders if the user explicitly says they want people outside their organization to use the plugin.
> You can mention this is an option if it seems like the user wants to distribute the plugin externally, but do not proactively ask about this with AskUserQuestion.
When a plugin is intended to be shared with others outside their company, it might have parts that need to be adapted to individual users.
You might need to reference external tools by category rather than specific product (e.g., "project tracker" instead of "Jira").
When sharing is needed, use generic language and mark these as requiring customization with two tilde characters such as `create an issue in ~~project tracker`.
If used any tool categories, write a `CONNECTORS.md` file at the plugin root to explain:
```markdown
# Connectors
## How tool references work
Plugin files use `~~category` as a placeholder for whatever tool the user
connects in that category. Plugins are tool-agnostic — they describe
workflows in terms of categories rather than specific products.
## Connectors for this plugin
| Category | Placeholder | Options |
| --------------- | ------------------- | ------------------------------- |
| Chat | `~~chat` | Slack, Microsoft Teams, Discord |
| Project tracker | `~~project tracker` | Linear, Asana, Jira |
```
### ${CLAUDE_PLUGIN_ROOT} Variable
Use `${CLAUDE_PLUGIN_ROOT}` for all intra-plugin path references in hooks and MCP configs. Never hardcode absolute paths.
## Guided Workflow
When you ask the user something, use AskUserQuestion. Don't assume "industry standard" defaults are correct. Note: AskUserQuestion always includes a Skip button and a free-text input box for custom answers, so do not include `None` or `Other` as options.
### Phase 1: Discovery
**Goal**: Understand what the useConvert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.
Run nf-core bioinformatics pipelines (rnaseq, sarek, atacseq) on sequencing data. Use when analyzing RNA-seq, WGS/WES, or ATAC-seq data—either local FASTQs or public datasets from GEO/SRA. Triggers on nf-core, Nextflow, FASTQ analysis, variant calling, gene expression, differential expression, GEO reanalysis, GSE/GSM/SRR accessions, or samplesheet creation.
This skill should be used when scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific decisions. Use this skill when users ask to pitch a new research idea, work through a project problem, evaluate project risks, plan research strategy, navigate decision trees, or get help choosing what scientific problem to work on. Typical requests include "I have an idea for a project", "I'm stuck on my research", "help me evaluate this project", "what should I work on", or "I need strategic advice about my research".
Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics deconvolution with DestVI, (6) label transfer and reference mapping with scANVI/scArches, (7) RNA velocity with veloVI, or (8) any deep learning-based single-cell method. Triggers include mentions of scVI, scANVI, totalVI, PeakVI, MultiVI, DestVI, veloVI, sysVI, scArches, variational autoencoder, VAE, batch correction, data integration, multi-modal, CITE-seq, multiome, reference mapping, latent space.
Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing data quality, or following scverse/scanpy best practices for single-cell analysis.
Set up your bio-research environment and explore available tools. Use when first getting oriented with the plugin, checking which literature, drug-discovery, or visualization MCP servers are connected, or surveying available analysis skills before starting a new project.
>
Package an escalation for engineering, product, or leadership with full context. Use when a bug needs engineering attention beyond normal support, multiple customers report the same issue, a customer is threatening to churn, or an issue has sat unresolved past its SLA.