Enforce a spec-driven development workflow for building features: automatically generate requirements, design, and task files from specifications, implement using TDD, and verify against requirements with remediation.
Fast-track interaction with a feature — quick edits, questions, or updates using existing artifacts
Analyse existing codebase to extract patterns, interfaces, flows, and conventions
Generate cross-cutting design artefact (design.md) with architecture, data models, interfaces, and decisions — without generating task files
Generate design.md plus hybrid task files in one combined flow
Show sddw workflow overview, list features, and check feature status
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sddwSpec-Driven Development Workflow for Claude Code.
design.md), then implement each task separately, then verify the result, then self-improve the workflow/clear context between steps — each step works within a focused context window--autoThe standard way to use AI coding agents is short, interactive prompts: describe what you want, get code, fix it, repeat. This works for small tasks but breaks down for anything non-trivial — context gets lost between sessions, architectural decisions live only in chat history, and there's no artifact a teammate can review before code is written.
sddw inverts this. Instead of prompting for code, you collaborate with the agent to write specifications — requirements, architecture, interface contracts, task breakdowns. The specs become the primary artifact: reviewable by peers, version-controlled, persistent across sessions. Code generation is then a mechanical step guided by approved specs, not a creative leap from a vague prompt.
Detailed specifications reduce AI code errors by up to 50% (Piskala, 2026), security defects by 73% (Marri, 2026), and architecture-misaligned PRs by 60% (GitHub Spec Kit). sddw is designed for medium to large projects that don't fit into a single context window. By splitting work into discrete steps — requirements, codebase analysis, design, per-task implementation — each step operates within a focused context where models are more accurate, rather than a sprawling conversation where critical details get lost.
git clone https://github.com/sermakarevich/sddw.git ~/.claude/sddw
cd ~/.claude/sddw && bash bin/install.sh
For development (symlink from local repo):
git clone https://github.com/sermakarevich/sddw.git
cd sddw && bash bin/install.sh --local
Every step supports two interaction modes:
| Mode | Flag | Behavior |
|---|---|---|
| Interactive | (default) | Full guided dialog — one question at a time, every section confirmed |
| Auto | --auto | Fully autonomous — no questions, best-judgment decisions |
Vibecoding — --auto. The agent decides everything.
Agentic engineering — default mode. You stay in control: review proposals, add missing context, ask questions, approve each spec section before it's written, and validate the output spec.
design.md with architecture, models, and decisionsdesign.md/sddw:design_and_taskify)/sddw:requirements <feature-name> [--auto]
Collaboratively produce a requirements spec through guided dialog:
Output: .sddw/<feature-name>/requirements.md
Sections: Purpose, User Stories, Functional Requirements, Acceptance Criteria, Constraints
/sddw:code-analysis <feature-name> [--auto]
Analyse the existing codebase to ground design decisions in reality:
npx claudepluginhub sermakarevich/sddwSpec-driven development pipeline for Claude Code: interview-to-spec, spec-approach, tdd, verify, diagnose, and a feature orchestrator.
Spec Driven Development toolkit - structured specification, planning, and implementation workflows for systematic feature development
Spec-driven development using GitHub spec-kit methodology. Constitution-first approach with specify, plan, tasks, and implement phases.
Specification-Driven Development with Process Discipline for Claude Code
Specification-driven development workflow: specify → plan → tasks → implement
Spec-driven development workflow - transforms ideas into structured specifications (requirements, design, tasks) before implementation.