OpenSpec — Spec-Driven AI Development

What it is

OpenSpec is a specification framework that gives AI coding agents structured instructions to follow when generating code. Instead of relying on ad-hoc prompts, you write formal specs that define architecture, coding standards, file structure, and behavior. AI agents like Cursor, Claude Code, and Copilot then follow these specs to produce consistent output.

This tool targets development teams who use AI coding assistants daily and want reproducible results across team members and sessions. It ships under the MIT license.

How it saves time or tokens

Without specs, developers repeat the same instructions in every prompt: use this framework, follow this pattern, name files this way. OpenSpec centralizes those instructions into reusable spec files. The estimated token cost is around 420 tokens per session. The real savings come from reduced iteration: agents get it right on the first try more often when following a clear spec.

How to use

1. Install OpenSpec or add spec files to your project root.
2. Define your project specifications in .openspec files.
3. Point your AI coding agent to the spec directory.
4. The agent reads specs before generating code.

# Initialize OpenSpec in your project
npx openspec init

# This creates .openspec/ directory with template files
# Edit the specs to match your project conventions

Example

A typical spec file:

# .openspec/architecture.yaml
name: my-api
framework: express
language: typescript
patterns:
  - name: route-handler
    template: |
      import { Router } from 'express'
      import { validate } from '../middleware/validate'
      
      const router = Router()
      
      router.post('/', validate(schema), async (req, res) => {
        const result = await service.create(req.body)
        res.status(201).json(result)
      })
      
      export default router
    rules:
      - Always use async/await, never callbacks
      - Validate input with middleware, not in handler
      - Return proper HTTP status codes

Related on TokRepo

• AI coding tools — More tools for AI-assisted development
• Prompt library — Reusable prompts and templates

Common pitfalls

• Specs that are too detailed become maintenance burdens. Keep them at the right abstraction level: conventions and patterns, not line-by-line templates.
• Different AI agents interpret specs with varying fidelity. Test your specs across agents before standardizing.
• Spec files add context tokens to every request. Keep total spec size reasonable to avoid hitting context limits.
• OpenSpec works best for greenfield projects. Retrofitting specs onto legacy codebases requires careful alignment with existing patterns.
• Version your spec files alongside code. Specs that drift from actual code cause agent confusion.