Spec-Driven Steroids

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

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 | | 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, commands, skills | | Qwen Code | user / project | Agents, commands, skills |

Installation

npm install -g spec-driven-steroids

Requirements:

• Node.js >=20

The CLI provides two command names:

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

CLI Usage

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

# Persist a new rule
sds stewardship store architecture --content "Use hexagonal architecture"

# 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>

# Retrieve context for a spec phase
sds stewardship inject design

# List, deprecate, or archive rules
sds stewardship manage list
sds stewardship manage deprecate --ruleId <ruleId>

These rules are automatically referenced by each spec-driven skill to give agents awareness of established project patterns.

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

2. Generate project guidance:

/inject-guidelines

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

3. Start the spec flow:

• GitHub Copilot: @spec-driven Add a rate limiter
• OpenCode: use the Spec-Driven agent
• Antigravity: /spec-driven
• Codex: /spec-driven Add a rate limiter

4. 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 Contents

dist/              # Built CLI and validation modules
templates/          # Platform templates and universal skills
README.md
LICENSE

Links

• npm: https://www.npmjs.com/package/spec-driven-steroids
• Repository: https://github.com/lindoelio/spec-driven-steroids
• Issues: https://github.com/lindoelio/spec-driven-steroids/issues

License

MIT