specs.md vs GitHub Spec Kit

Compare specs.md with GitHub's Spec Kit toolkit

Overview

GitHub Spec Kit is a toolkit that provides agent prompts and 7 slash commands (/speckit.constitution, /speckit.specify, /speckit.plan, /speckit.tasks, /speckit.analyze, /speckit.implement, /speckit.clarify) for 15+ AI coding assistants including Claude Code, Cursor, GitHub Copilot, and Gemini CLI.

specs.md is a full methodology implementation with phase-based agents, Mob rituals, and DDD integration.

Side-by-Side Comparison

Aspect	specs.md	Spec Kit
Type	Full methodology	Toolkit + Agent Prompts
Target	Complex systems requiring trade-offs	Small-medium projects
Approach	Structured AI-DLC phases with methodology	6-phase workflow with agent prompts
Structure	Intents → Units → Stories	Constitution → Specify → Plan → Tasks → Analyze → Implement
Agent Model	3 phase-based agents	Prompts for 15+ AI assistants
Design Integration	DDD default (extensible via bolt types)	Constitution file
Rituals	Mob Elaboration, Mob Construction	None
Memory	Memory Bank (persistent context)	Constitution file + .specify folder
Customization	Skills, templates, memory bank	Constitution file, scripts, templates
Learning Curve	Moderate	Low
VS Code Extension	Yes (visual dashboard)	No

When to Choose Each

Choose specs.md (AI-DLC) if:

You’re building complex systems with architectural trade-offs
You need DDD integration and domain modeling
You want Mob rituals for team alignment
You have multiple teams needing coordination
You want a proven AWS methodology
You want a VS Code extension to track progress visually

Choose Spec Kit if:

You want minimal workflow change
You’re working on simpler projects
You prefer command-driven interaction
You want the lowest learning curve
You want minimal ceremony

Key Differences

1. Methodology vs Toolkit

Spec Kit is a toolkit—a set of commands that structure your prompts. It doesn’t prescribe how you work, just helps you write better specs.

specs.md is a full methodology with:

Defined phases (Inception → Construction → Operations)
Rituals (Mob Elaboration, Mob Construction)
Role definitions (AI drives, human validates)
Artifact specifications (Intents, Units, Bolts)

2. Conversation Direction

Spec Kit: Agent-driven via structured prompts

Human: /speckit.specify [high-level description]
AI: [generates detailed specification with user journeys]
AI: [asks clarifying questions via /speckit.clarify]
Human: [validates and refines]

specs.md: AI drives with Mob rituals

Human: [provides intent]
AI: "I've analyzed your intent. Here are 3 Units I propose.
     I have 5 clarifying questions before we proceed..."
Human: [validates, approves, or redirects in Mob session]

3. Design Integration

Spec Kit: Constitution file sets project principles and constraints. Technical plan phase handles architecture decisions.

specs.md: DDD is the default methodology. AI applies domain-driven design principles during decomposition, creating bounded contexts, aggregates, and domain models. Extensible via bolt types for BDD, TDD, or custom flows.

AI-DLC’s Opinionated Approach

Unlike toolkit-based approaches, AI-DLC is an opinionated methodology with specific patterns:

Bolts, Not Sprints: Instead of 2-week sprints with variable scope, AI-DLC uses Bolts—focused execution units measured in hours or days. Each Bolt batches related stories together and executes them with full DDD construction steps.

DDD Baked In: Domain-Driven Design isn’t optional—it’s integral. Every Bolt follows DDD patterns: domain modeling, bounded contexts, aggregates, and entities. This creates consistent, high-quality designs regardless of who’s working.

Agent Drives, Human Validates: In AI-DLC, the AI proposes breakdown, trade-offs, and designs. Humans validate and approve. This reversed conversation direction keeps humans in control while leveraging AI’s synthesis capabilities.

Full Traceability: Artifacts created during construction show exactly what was built and how—from Intent to Unit to Story to Bolt execution.

Migration Path

If you’re currently using Spec Kit and want more structure:

Start with Simple Flow

specs.md (Simple Flow) provides Kiro-style Requirements → Design → Tasks workflow

Add Memory Bank

Enable persistent context across sessions

Adopt Phase Structure

Organize work into Inception, Construction, Operations

Graduate to Full AI-DLC

When complexity demands it, adopt full Mob rituals and DDD integration

Summary

For This Need	Use This
Quick spec generation	Spec Kit or specs.md (Simple Flow)
Minimal learning curve	Spec Kit
Complex system development	specs.md
Team coordination	specs.md
Enterprise/regulated environments	specs.md
DDD integration	specs.md