# Get Shit Done

> Structured execution workflow for managing large projects through planning, task decomposition, progress tracking, and iterative implementation.

- Skill: `anantsharma67/get-shit-done` (Agent Skill)
- Install (CLI): `npx skillmds@latest add anantsharma67/get-shit-done`
- Raw SKILL.md: https://api.skillmd.com/api/skills/anantsharma67/get-shit-done/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Productivity
- Author: anantsharma67 (https://skillmd.com/u/anantsharma67)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/anantsharma67/get-shit-done

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# Get Shit Done (GSD)

## Overview

This skill provides a comprehensive workflow for executing large and complex projects with minimal chaos.

It focuses on breaking projects into manageable steps, maintaining documentation, and reducing debugging through structured execution.

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## Setup

Before using this skill:

1. Define the project goal
2. Create a workspace for:
   - documentation
   - task tracking
   - progress logs

Recommended tools:
- GitHub Projects
- Markdown documentation
- Kanban boards
- Issue tracking systems

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## Inputs Required

- Project idea or objective
- Requirements or constraints
- Timeline or priorities (optional)

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## When to Use This Skill

- Large software projects
- Multi-step workflows
- Long-term execution planning
- Complex implementation tasks
- Team coordination

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## When NOT to Use

- Tiny one-step tasks
- Quick experiments
- Highly exploratory brainstorming sessions

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## Example Use Case

> “Build a full-stack AI application with authentication and deployment”

Claude should:

1. Break project into phases
2. Create implementation roadmap
3. Define milestones
4. Generate task-by-task execution plan
5. Track progress continuously

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## Workflow

### 1. Project Definition
- Define end goal
- Clarify constraints
- Identify major components

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### 2. Task Decomposition
Break project into:
- modules
- milestones
- subtasks
- dependencies

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### 3. Execution Planning
- Prioritize tasks
- Estimate complexity
- Define deliverables

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### 4. Implementation
- Execute incrementally
- Validate after each stage
- Document decisions

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### 5. Tracking & Iteration
- Monitor progress
- Detect blockers early
- Refine plans dynamically

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## Output Expectations

- Structured execution roadmap
- Clear task hierarchy
- Reduced implementation chaos
- Better debugging and maintainability

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## Execution Strategy (for AI agents)

The agent should:

1. Prevent scope chaos
2. Break large problems into manageable tasks
3. Maintain structured documentation
4. Track dependencies continuously
5. Validate progress incrementally

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## Best Practices

- Avoid implementing everything at once
- Document decisions early
- Validate small increments frequently
- Keep tasks independently testable

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## Notes

- Large projects fail primarily from poor structure
- Incremental execution reduces debugging overhead
- Good documentation improves long-term maintainability