ai-writing-guide

🥈Silver

AI writing guide automates software development workflows. It uses 94 specialized agents and 65+ commands for multi-agent coordination. Reduces manual oversight and extends runtime. Integrates with Claude Code, Warp, and Factory AI.

7180Updated 1mo ago

Intermediate30min to implementautomation

Saves ~300 min per use

Quick InstallView Source

git clone https://github.com/jmagly/ai-writing-guide.git

Works with:

Claude

Overview

About This Skill

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/jmagly/ai-writing-guide

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

Act as an autonomous coding agent. You are part of a team of 94 specialized agents working on a project for [COMPANY] in the [INDUSTRY] sector. Use the 65+ available workflow commands to coordinate with other agents. Your goal is to complete the task with minimal human intervention. Current task: [TASK]. Provide a detailed plan with clear steps and expected outcomes.

Example Output

# Autonomous Coding Agent Plan

## Task: Implement User Authentication System

### Step 1: Requirements Gathering
- **Agent Coordination**: Assign Agent 12 (Requirements Analyst) to gather and document user authentication requirements.
- **Workflow Command**: Use `gather_requirements` command with parameters: `scope=user_authentication, industry=[INDUSTRY]`.
- **Expected Outcome**: Detailed requirements document with functional and non-functional requirements.

### Step 2: System Design
- **Agent Coordination**: Assign Agent 34 (System Architect) to design the authentication system.
- **Workflow Command**: Use `design_system` command with parameters: `requirements=requirements_doc, tech_stack=Python_Django_React`.
- **Expected Outcome**: System architecture diagram and design document.

### Step 3: Implementation
- **Agent Coordination**: Assign Agents 15, 27, and 48 (Backend, Frontend, and Database Specialists) to implement the system.
- **Workflow Command**: Use `implement_system` command with parameters: `design=design_doc, team=backend_frontend_db`.
- **Expected Outcome**: Functional user authentication system integrated with the existing application.

### Step 4: Testing
- **Agent Coordination**: Assign Agent 56 (QA Engineer) to test the implemented system.
- **Workflow Command**: Use `test_system` command with parameters: `system=user_authentication, test_cases=standard_auth_test_cases`.
- **Expected Outcome**: Test report with pass/fail status and any identified issues.

### Step 5: Deployment
- **Agent Coordination**: Assign Agent 78 (DevOps Engineer) to deploy the system.
- **Workflow Command**: Use `deploy_system` command with parameters: `system=user_authentication, environment=production`.
- **Expected Outcome**: Successfully deployed user authentication system with minimal downtime.