Spec-Driven Development Workflow for Claude Code: Decomposition, Context Clearing, and Cost Control

A new open-source plugin called Spec Driven Development Workflow (SDDW) aims to improve Claude Code's performance on complex tasks through structured decomposition and context management. The approach, shared on Hacker News by developer sermakarevich, is designed for mid-to-large projects where Claude's built-in plan + code mode falls short.
Key Concepts
- Two-dimensional decomposition: First, generate specs in multiple steps (requirements, code analysis, design). Then split the implementation into subtasks and execute them one by one.
- Context clearing between every step: After spec generation and after each subtask implementation, the context is wiped. This keeps costs low and focused, boosting performance.
- Specs written to disk: Persistent spec files maintain information across sessions, preventing loss when context is cleared.
- Layer-by-layer delivery: Deliver specs incrementally to catch misunderstandings early.
When to Use It
According to the author, SDDW is not a replacement for Claude's plan + code mode when that works well. It's for scenarios where plan + code fails because the feature is too complicated. The double decomposition helps reduce confusion and improves success rates on complex tasks.
The author also notes that SDDW works well with a fleet of agents — you can insert the sequence of SDDW steps into a queue and let multiple agents handle subtasks.
Comparison to Other Tools
Compared to tools like GSD (Generalized Spec-Driven Development), SDDW is tailored for mid-size projects. GSD was great but token-heavy for smaller tasks. SDDW allows adjustments to typical project sizes.
Critiques from the Community
Some HN commenters raised concerns:
- Agent adherence and laziness — even with a detailed spec, agents may still produce outputs that require significant sanding and polishing.
- No formal benchmarks — the author acknowledges that measuring success is subjective, but claims that when plan + code fails and SDDW works, it's a net gain.
- Specs as non-runnable code — a detailed enough spec is nearly equivalent to code, so the overhead may not always be justified.
Getting Started
The plugin is available on GitHub: github.com/sermakarevich/sddw. Slides with more details are linked in the HN discussion.
📖 Read the full source: HN AI Agents
👀 See Also

Claude Code Plugin Yoink Replaces Library Dependencies to Reduce Supply Chain Risk
Yoink is a Claude Code plugin that removes complex dependencies by reimplementing only needed functions, using a three-step workflow with /setup, /curate-tests, and /decompose commands. It currently supports Python with TypeScript and Rust support underway.

CADAM: Open-Source Text-to-CAD with Parametric Sliders and WebAssembly Rendering
CADAM generates parametric 3D models from text or images, outputs OpenSCAD code with interactive sliders, and runs fully in browser via WebAssembly.

Intuno: Open-Sourced Network for AI Agent Discovery and Communication
Intuno is an open-source network where AI agents register capabilities, discover each other via semantic search, and invoke functions with 3 lines of Python code. It includes MCP integration for use with Claude Desktop or Cursor.

VS Code Agent Kanban: Markdown-based task management for AI coding agents
VS Code Agent Kanban is an extension that creates a GitOps-friendly kanban board inside VS Code using markdown files as task records. It addresses context rot in AI coding agents by preserving planning conversations, decisions, and implementation details in version-controlled .md files.