By fuww
Write SQL, explore datasets, and generate insights faster. Build visualizations and dashboards, and turn raw data into clear stories for stakeholders. Configured for FashionUnited with BigQuery data warehouse, Looker Studio dashboards, and Plausible analytics.
Answer data questions -- from quick lookups to full analyses
Build an interactive HTML dashboard with charts, filters, and tables
Create publication-quality visualizations with Python
Profile and explore a dataset to understand its shape, quality, and patterns
Generate fashion industry market reports from BigQuery and GraphQL API data
Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts. BOOTSTRAP MODE - Triggers: "Create a data context skill", "Set up data analysis for our warehouse", "Help me create a skill for our database", "Generate a data skill for [company]" → Discovers schemas, asks key questions, generates initial skill with reference files ITERATION MODE - Triggers: "Add context about [domain]", "The skill needs more info about [topic]", "Update the data skill with [metrics/tables/terminology]", "Improve the [domain] reference" → Loads existing skill, asks targeted questions, appends/updates reference files Use when data analysts want Claude to understand their company's specific data warehouse, terminology, metrics definitions, and common query patterns.
Profile and explore datasets to understand their shape, quality, and patterns before analysis. Use when encountering a new dataset, assessing data quality, discovering column distributions, identifying nulls and outliers, or deciding which dimensions to analyze.
QA an analysis before sharing with stakeholders — methodology checks, accuracy verification, and bias detection. Use when reviewing an analysis for errors, checking for survivorship bias, validating aggregation logic, or preparing documentation for reproducibility.
Create effective data visualizations with Python (matplotlib, seaborn, plotly). Use when building charts, choosing the right chart type for a dataset, creating publication-quality figures, or applying design principles like accessibility and color theory.
Fashion industry domain knowledge for data analysis and content creation. Includes fashion week calendars (Paris, Milan, London, New York, etc.), trade fair schedules (Premiere Vision, Texworld, ISPO, Pitti), seasonal planning cycles, and industry terminology. Use when analyzing fashion data, creating editorial calendars, writing fashion content, or interpreting market trends.
External network access
Connects to servers outside your machine
Requires secrets
Needs API keys or credentials to function
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Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
FashionUnited Fork — This is a customized version of Anthropic's knowledge-work-plugins, adapted for FashionUnited's tools, workflows, and fashion industry context. Licensed under Apache 2.0.
Plugins that turn Claude into a specialist for your role, team, and company. Built for Claude Cowork, also compatible with Claude Code.
Cowork lets you set the goal and Claude delivers finished, professional work. Plugins let you go further: tell Claude how you like work done, which tools and data to pull from, how to handle critical workflows, and what slash commands to expose — so your team gets better and more consistent outcomes.
Each plugin bundles the skills, connectors, slash commands, and sub-agents for a specific job function. Out of the box, they give Claude a strong starting point for helping anyone in that role. The real power comes when you customize them for your company — your tools, your terminology, your processes — so Claude works like it was built for your team.
We're open-sourcing 10 plugins built and inspired by our own work:
| Plugin | How it helps | FashionUnited Connectors | MCP |
|---|---|---|---|
| productivity | Manage tasks, calendars, daily workflows, and personal context for fashion industry professionals. | Google Chat, Google Workspace, GitHub, beads | ✓✓✓— |
| sales | Research advertisers, prep for calls, manage B2B pipeline, draft outreach for fashion brands. | Google Chat, Vtiger CRM, Google Workspace | ✓✓✓ |
| customer-support | Triage tickets from advertisers and employers, research account context, build FAQ content. | Google Chat, Vtiger CRM, Google Workspace | ✓✓✓ |
| product-management | Write specs, plan roadmaps, synthesize user research for fashion B2B products. | Google Chat, GitHub, Google Workspace, Figma, Plausible | ✓✓✓✓✓ |
| marketing | Draft fashion news, plan content campaigns, manage newsletters, track performance across markets. | Google Chat, Mailchimp, Social Champ, Plausible, Google Search Console, Figma | ✓✓✗✓✓✓ |
| legal | Review advertising agreements, media partnerships, GDPR compliance across 30+ markets. | Google Workspace | ✓ |
| finance | Advertising revenue, subscription billing, multi-currency operations across markets. | BigQuery, Google Workspace, Vtiger CRM | ✓✓✓ |
| data | Query jobs, marketplace, editorial data — SQL templates for FashionUnited metrics. | BigQuery, Looker Studio, Plausible, Google Workspace | ✓✓✓✓ |
| enterprise-search | Find anything across email, chat, docs, CRM, code — brand lookup, job history, editorial archives. | Google Chat, Google Workspace, GitHub, Vtiger CRM, BigQuery | ✓✓✓✓✓ |
| cowork-plugin-management | Create new plugins or customize existing ones with FashionUnited tool stack and domain knowledge. | — | — |
MCP column shows support status per connector in order: ✓ = MCP server available, ✗ = no MCP available, — = not applicable
Install these directly from Cowork, browse the full collection here on GitHub, or build your own.
# Install from the plugin marketplace
claude plugins add knowledge-work-plugins
# Or install a specific plugin
claude plugins add knowledge-work-plugins/sales
Once installed, plugins activate automatically. Skills fire when relevant, and slash commands are available in your session (e.g., /sales:call-prep, /data:write-query).
Every plugin follows the same structure:
plugin-name/
├── .claude-plugin/plugin.json # Manifest
├── .mcp.json # Tool connections
├── commands/ # Slash commands you invoke explicitly
└── skills/ # Domain knowledge Claude draws on automatically
/finance:reconciliation, /product-management:write-spec).Every component is file-based — markdown and JSON, no code, no infrastructure, no build steps.
These plugins are generic starting points. They become much more useful when you customize them for how your company actually works:
npx claudepluginhub fuww/knowledge-work-pluginsManage tasks, plan your day, and build up memory of important context about your work for fashion industry professionals. Syncs with your calendar, email, and chat to keep everything organized and on track.
Search across all FashionUnited tools in one place. Find anything across email, chat, documents, code repositories, CRM, and data warehouse — brand information, editorial archives, job market data, and marketplace catalogs.
Create content, plan campaigns, and analyze performance for fashion media operations across 30+ markets. Maintain brand voice consistency in 9 language editions, track competitors, and report on what's working.
Write SQL, explore datasets, and generate insights faster. Build visualizations and dashboards, and turn raw data into clear stories for stakeholders.
Connect to Looker and interact with your data using LookML.
AI-powered product analytics: ask a business question, get validated findings, publication-quality charts, and a slide deck.
Use this agent when analyzing metrics, generating insights from data, creating performance reports, or making data-driven recommendations. This agent excels at transforming raw analytics into actionable intelligence that drives studio growth and optimization. Examples:\n\n<example>\nContext: Monthly performance review needed
Use this agent when analyzing metrics, generating insights from data, creating performance reports, or making data-driven recommendations. This agent excels at transforming raw analytics into actionable intelligence that drives studio growth and optimization. Examples:\n\n<example>\nContext: Monthly performance review needed
Data & metrics skills: Data Analysis Standard, Retention Analysis, Product Health Analysis. Structure metric deep-dives, funnel analysis, cohort studies and churn investigations.