Claude-Code-Zen-mcp-Skill-Work

🥈Silver

Claude-Code-Zen-mcp-Skill-Work is a pre-built rule system and skill package for AI programming agents. It enables developers to quickly implement standardized workflows for AI-driven automation tasks. Operations teams benefit from reduced setup time and consistent execution across various automation projects.

11580Updated 2w ago

Intermediate30min to implementautomation

Saves ~5 min per use

Quick InstallView Source

git clone https://github.com/VCnoC/Claude-Code-Zen-mcp-Skill-Work.git

Works with:

Claude

Overview

About This Skill

How to Use

[{"step":"Define the automation task and inputs","action":"Use the prompt template to specify [PROJECT_NAME], [AUTOMATION_TASK], [INPUT_SOURCES], and [OUTPUT_DESTINATIONS]. For example, replace [AUTOMATION_TASK] with 'daily_inventory_sync' and [INPUT_SOURCES] with 'ERP system API and CSV export'.","tip":"Use the MCP CLI to validate your configuration file before execution: `claude-code-zen-mcp validate --config your_config.yaml`"},{"step":"Configure validation rules","action":"Add [VALIDATION_RULES] to ensure data quality. Include checks for null values, schema validation, and data freshness. For example, set `data_freshness: last_24h` for real-time syncs.","tip":"Pre-built rule templates are available in the `claude-code-zen-mcp-rules` repository. Reference them in your config file."},{"step":"Set up reporting metrics","action":"Define [REPORTING_METRICS] in your config file to track KPIs. For a marketing automation project, include metrics like 'click_through_rate' and 'conversion_to_lead'.","tip":"Use the MCP dashboard to visualize metrics: `claude-code-zen-mcp dashboard --config your_config.yaml`"},{"step":"Execute and monitor","action":"Run the workflow using the MCP CLI: `claude-code-zen-mcp run --config your_config.yaml`. Monitor execution logs and validate outputs.","tip":"Enable notifications in your config file to receive alerts for failures: `notifications: [\"slack://#automation-alerts\", \"email://team@company.com\"]`"},{"step":"Iterate and optimize","action":"Review the validation report and adjust rules or metrics as needed. For example, if data freshness fails frequently, reduce the threshold to `last_48h`.","tip":"Use the MCP audit log to track changes: `claude-code-zen-mcp audit --project your_project_name`"}]

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/VCnoC/Claude-Code-Zen-mcp-Skill-Work

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Implement a standardized AI-driven automation workflow for [PROJECT_NAME] using the Claude-Code-Zen-mcp-Skill-Work framework. Follow the pre-built rule system to: 1) Set up [AUTOMATION_TASK], 2) Define [INPUT_SOURCES] and [OUTPUT_DESTINATIONS], 3) Apply [VALIDATION_RULES], and 4) Generate [REPORTING_METRICS]. Use the MCP (Model Context Protocol) to ensure seamless integration with [TARGET_SYSTEM].

Example Output

Here’s the implementation for automating a weekly data pipeline for Acme Corp’s sales analytics:

**1. Setup & Configuration**
- Created a `claude-code-zen-mcp-workflow.yaml` file with the following structure:
  ```yaml
  project: acme_sales_automation
  automation_task: weekly_sales_report
  input_sources:
    - type: csv
      path: /data/raw/sales_transactions.csv
    - type: API
      endpoint: https://api.acme.com/sales/leads
  output_destinations:
    - type: database
      table: weekly_sales_summary
    - type: email
      recipients: ["analytics@acme.com", "sales@acme.com"]
  validation_rules:
    - check_null_values: true
    - validate_schema: sales_schema_v2.json
    - data_freshness: last_7_days
  reporting_metrics:
    - total_revenue
    - top_10_deals
    - conversion_rate
  ```

**2. Execution**
- Ran the workflow using the MCP CLI:
  ```bash
  claude-code-zen-mcp run --config claude-code-zen-mcp-workflow.yaml
  ```
  Output:
  ```
  [2024-05-10 14:22:33] INFO: Starting workflow 'acme_sales_automation'
  [2024-05-10 14:22:35] INFO: Loaded 12,487 records from sales_transactions.csv
  [2024-05-10 14:22:37] INFO: Fetched 456 leads from API
  [2024-05-10 14:22:40] INFO: Validated data against schema (0 errors)
  [2024-05-10 14:22:42] INFO: Generated weekly sales summary
  [2024-05-10 14:22:45] INFO: Exported to database and sent to 2 recipients
  [2024-05-10 14:22:45] SUCCESS: Workflow completed in 12.3s
  ```

**3. Validation & Reporting**
- Generated a validation report:
  ```
  Validation Summary:
  - Null values: 0 (100% compliance)
  - Schema compliance: 100%
  - Data freshness: 100% (last 7 days)
  
  Key Metrics:
  - Total Revenue: $2,456,789
  - Top 10 Deals: 8 closed, 2 pending
  - Conversion Rate: 15.2% (up 2.1% from last week)
  ```

The workflow now runs automatically every Monday at 8 AM, reducing manual effort by 80% and ensuring consistent data quality for Acme’s sales team.