Where is the workflow progress data stored?

All workflow state, including task lists, decisions made, and agent history, is stored locally in '.claude/claude-bot.local.md'.

How does this skill handle parallel tasks?

During the Explore and Validate phases, the skill launches multiple sub-agents simultaneously to analyze the codebase or review code faster.

Can I resume a workflow if it gets interrupted?

Yes, the skill maintains state in a local markdown file, allowing you to resume any paused or blocked workflow from exactly where it left off.

What are the 7 phases of the autonomous workflow?

The workflow follows a structured path through Planning, Exploration, Design, Implementation, Validation, Testing, and Documentation to ensure complete task coverage.

What happens if the AI encounters a blocker?

When a blocker is detected, the skill saves the current state, updates the status to 'blocked', and presents the issue to the user for resolution before resuming.

Autonomous Development Workflow

Name: Autonomous Development Workflow
Author: siliconagent

bysiliconagent

•

Productivity & Workflow

Orchestrates a comprehensive 7-phase autonomous development lifecycle with persistent state management and multi-agent coordination.

About

This skill empowers Claude Code to function as an autonomous software engineer by implementing a structured 7-phase development cycle: Plan, Explore, Design, Implement, Validate, Test, and Document. It utilizes a sophisticated state-management system stored in a local markdown file, allowing complex workflows to be paused, resumed, and audited. By leveraging parallel execution for exploration and validation alongside sequential logic for architectural design, this skill ensures that development tasks are handled with professional-grade rigor and consistency.

Key Features

Persistent State Management for Resumable Workflows
Automated Blocker Detection and User-Resolution Flow
7-Phase SDLC Automation (Plan to Document)
Parallel Agent Execution for Codebase Exploration and Validation
Detailed Agent History and Decision Logging
1 GitHub stars

Use Cases

Executing complex feature requests that require deep architectural planning and testing.
Automating large-scale codebase refactoring with multi-step validation.
Managing long-running development tasks that need to persist across different sessions.

About

Key Features

Persistent State Management for Resumable Workflows
Automated Blocker Detection and User-Resolution Flow
7-Phase SDLC Automation (Plan to Document)
Parallel Agent Execution for Codebase Exploration and Validation
Detailed Agent History and Decision Logging
1 GitHub stars

Use Cases

Executing complex feature requests that require deep architectural planning and testing.
Automating large-scale codebase refactoring with multi-step validation.
Managing long-running development tasks that need to persist across different sessions.