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Spec-Driven Steroids

Inject Spec-Driven Development into AI coding tools without building a new UI.

npm version License: MIT

What it is

spec-driven-steroids is a CLI plus template bundle for running a strict workflow inside AI coding tools:

requirements → design → tasks → implementation

It injects:

  • Platform-specific agents, commands, or workflows
  • Universal writing/implementation skills
  • CLI validation commands for spec structure and traceability
  • A knowledge graph for architectural decisions and business rules

Supported Platforms

Platform Scope Injection Type
Antigravity project /spec-driven workflow
Claude Code project Agents, commands, skills
Cline user / project Agents, commands, skills
Gemini CLI global / project Agents, commands, skills
GitHub Copilot CLI user / project Agents, commands, skills
GitHub Copilot for VS Code global / project Agents, prompts, skills
GitHub Copilot for JetBrains project Agents, prompts, skills
OpenCode global / project Agents, commands, skills
OpenAI Codex project Agents, command skills, skills
Qwen Code user / project Agents, commands, skills

Installation

npm install -g spec-driven-steroids

Requirements:

  • Node.js >=20
  • pnpm for local development

CLI Usage

The CLI provides two command names:

  • sds (short alias - recommended)
  • spec-driven-steroids (full name)

Inject Command

# Interactive injection (prompts for platform and scope)
sds inject

Validate Commands

# Validate spec folder structure
sds validate structure <slug>

# Validate EARS requirements
sds validate requirements <path>

# Validate design structure and Mermaid
sds validate design <path>

# Validate task structure and traceability
sds validate tasks <path>

# Full end-to-end validation
sds validate spec <slug>

Other Commands

# Clean globally injected steroids
sds clean --global

# Show version
sds --version

# Show help
sds --help

Stewardship Commands

Manage a knowledge graph of architectural decisions, business rules, and workflow conventions extracted from spec files:

# Report available stewardship capabilities
sds stewardship capabilities

# Search for rules in the knowledge graph
sds stewardship retrieve <query> --domain architecture [--scope <project-id>] [--global]

# Persist a project-scoped rule by default
sds stewardship store architecture --content "Use hexagonal architecture"

# Persist a truly universal rule
sds stewardship store workflow --content "Run typecheck before completion" --global

# Extract decision candidates from a design.md or requirements.md
sds stewardship extract .specs/changes/my-feature/design.md

# Show rule provenance and version history
sds stewardship trace <ruleId> [--scope <project-id>] [--global]

# Retrieve context for a spec phase
sds stewardship inject design [--scope <project-id>] [--global]

# List, deprecate, archive, or move rules
sds stewardship manage list
sds stewardship manage deprecate --ruleId <ruleId> [--scope <project-id>] [--global]
sds stewardship manage move --ruleId <ruleId> --scope <project-id>

Rules are project-scoped by default and only fall back to global rules during retrieval. Use --global only for memories that are safe across unrelated repositories.

Skills Injected

The CLI injects these universal skills that work across all platforms:

Core Spec-Driven Skills

Skill Purpose Phase
spec-driven-requirements-writer Write EARS-format requirements 1
spec-driven-technical-designer Create technical design with Mermaid 2
spec-driven-task-decomposer Decompose into atomic tasks 3
spec-driven-task-implementer Execute tasks from tasks.md 4

Universal Skills

Skill Purpose
contextual-stewardship Knowledge graph for architectural decisions
quality-grading Grade code/specs across 4 dimensions
code-review-hardening Structured code review with self-repair
universal-live-check Real-time validation framework
long-running-work-planning Durable checkpointed execution for long tasks
project-guidelines-writer Generate repository guidelines
agent-work-auditor Audit agent-generated artifacts

Agents Injected

Agent Purpose
spec-driven Main spec-driven workflow orchestrator

Spec Flow

What gets generated

Spec-Driven planning writes artifacts to:

.specs/changes/<slug>/
├── requirements.md
├── design.md
└── tasks.md

Workflow phases

  1. Requirements - EARS-syntax requirements with stable IDs
  2. Design - Mermaid diagrams, architecture sections
  3. Tasks - Atomic implementation tasks with traceability
  4. Implementation - Task execution with verification

Quick start

  1. Inject platform files into a repository:
sds inject
  1. Generate project guidance:
/inject-guidelines

This creates: AGENTS.md, CONTRIBUTING.md, STYLEGUIDE.md, TESTING.md, ARCHITECTURE.md, SECURITY.md

  1. Start the spec flow:
  • GitHub Copilot: @spec-driven Add a rate limiter
  • OpenCode: use the Spec-Driven agent
  • Cline: use the Spec-Driven agent or /spec-driven
  • Antigravity: /spec-driven
  • Codex: select the spec-driven skill with /skills or mention $spec-driven
  1. Approve each planning phase, then move to implementation.

Long-Running Work

For complex long-running tasks, SDS injects long-running-work-planning. It keeps agents working through durable artifacts, task status updates, checkpoints, and verification.

Package Layout

packages/
├── cli/                    # Main CLI package
│   ├── src/
│   │   ├── cli/           # Injection commands
│   │   ├── core/validate/ # Validation modules
│   │   └── context-stewardship/ # Knowledge graph
│   └── templates/          # Platform templates & skills
├── test-utils/             # Test fixtures and mocks
└── landing-page/         # Documentation site

Development

pnpm install
pnpm build
pnpm test

Useful commands:

  • pnpm typecheck - Type check all packages
  • pnpm lint - Lint all packages
  • pnpm test:coverage - Run tests with coverage
  • pnpm changeset - Create a changeset
  • pnpm changeset:version - Version bump

Repository Docs

License

MIT

About

Spec-Driven Steroids is a very simple toolkit designed to bring discipline to AI-powered software engineering. It injects high-standard workflows (SDD) directly into the native environments of your favorite AI tools.

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