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By sumeet138
ETL pipeline construction, data warehouse design, batch processing workflows, and data-driven feature development
npx claudepluginhub sumeet138/qwen-code-agents --plugin data-engineeringBuild features guided by data insights, A/B testing, and continuous measurement
You are a data pipeline architecture expert specializing in scalable, reliable, and cost-effective data pipelines for batch and streaming data processing.
Expert backend architect specializing in scalable API design, microservices architecture, and distributed systems. Masters REST/GraphQL/gRPC APIs, event-driven architectures, service mesh patterns, and modern backend frameworks. Handles service boundary definition, inter-service communication, resilience patterns, and observability. Use PROACTIVELY when creating new backend services or APIs.
Build scalable data pipelines, modern data warehouses, and real-time streaming architectures. Implements Apache Spark, dbt, Airflow, and cloud-native data platforms. Use PROACTIVELY for data pipeline design, analytics infrastructure, or modern data stack implementation.
Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.
Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.
Optimize Apache Spark jobs with partitioning, caching, shuffle optimization, and memory tuning. Use when improving Spark performance, debugging slow jobs, or scaling data processing pipelines.
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.
Data engineering agents providing expertise in ETL pipelines, streaming, and data warehousing
Editorial "Data Engineering" bundle for Claude Code from Antigravity Awesome Skills.
Data engineering, ML, and AI specialists - data pipelines, machine learning, LLM architecture
Data engineering and ETL tools. Includes 3 specialized agents, 4 commands, and 19 skills.
Agents for data engineering, machine learning, and AI development
Automated data preprocessing and cleaning pipelines
LLM application development with LangGraph, RAG systems, vector search, and AI agent architectures for Claude 4.6 and GPT-5.2
Interactive debugging, developer experience optimization, and smart debugging workflows
Distributed system tracing and debugging across microservices
REST and GraphQL API scaffolding, framework selection, backend architecture, and API generation
Technical SEO optimization including meta tags, keywords, structure, and featured snippets
Adapted for Qwen Code — 77 plugins, 182 agents, 149 skills, and 96 commands now working with Qwen 3.6
A comprehensive production-ready system combining 182 specialized AI agents, 16 multi-agent workflow orchestrators, 149 agent skills, and 96 commands organized into 77 focused, single-purpose plugins — adapted for Qwen Code.
This project is a fork/adaptation of claude-code-workflows by Seth Hobson (@wshobson).
All original plugin content, agent expertise, skill knowledge, command workflows, and architectural design are the work of Seth Hobson and contributors. This adaptation converts the plugin infrastructure to work with Qwen Code instead of Claude Code, while preserving 100% of the original content and intelligence.
Original repository: github.com/wshobson/agents Original license: MIT
Claude Code is expensive. Qwen Code is free (OAuth: 60 req/min, 1000/day) or very cheap (API key). This project brings the same powerful agent orchestration system to Qwen Code so you can use 182 specialized AI agents without paying for Claude.
| Aspect | Before (Claude Code) | After (Qwen Code) |
|---|---|---|
| Cost | $3+ per 1M tokens (Sonnet) | Free (OAuth) or ~$0.02/1M tokens |
| Model for critical tasks | Claude Opus 4.6 | Qwen-Max |
| Model for complex tasks | Claude Sonnet 4.6 | Qwen-Plus |
| Model for fast tasks | Claude Haiku 4.5 | Qwen-Flash |
| Plugins | 77 | 77 (same) |
| Agents | 182 | 182 (same expertise) |
| Skills | 149 | 149 (same knowledge) |
| Commands | 96 | 96 (same workflows) |
| Agent knowledge | Identical | Identical |
| Skill content | Identical | Identical |
| Workflow automation | Identical | Identical |
| Monthly savings | Baseline | ~99% cheaper |
| Component | Changed? | Details |
|---|---|---|
| Agent system prompts | No | All 182 agents have identical expertise |
| Skill knowledge packages | No | All 149 skills with progressive disclosure |
| Command workflows | No | All 96 workflow automations |
| Plugin structure | No | Same directory organization |
model: opus references | Yes | Mapped to model: qwen-max |
model: sonnet references | Yes | Mapped to model: qwen-plus |
model: haiku references | Yes | Mapped to model: qwen-flash |
| Plugin manifest | Yes | plugin.json + qwen-extension.json |
| Context files | Added | QWEN.md per plugin |
This unified repository provides everything needed for intelligent automation and multi-agent orchestration across modern software development:
Each plugin is completely isolated with its own agents, commands, and skills:
Example: Installing python-development loads 3 Python agents, 1 scaffolding tool, and makes 16 skills available (~1000 tokens), not the entire marketplace.