skyf0xx/hedgehog
HEDGEHOG codes Cleaner, Faster and with Fewer Tokens. Hedgehog's AI-driven development builds a task dependency graph from your spec-driven, BMAD-METHOD plan, so Claude Code, Cursor & Gemini CLI stay locked to it. A CLI-enforced state machine for agentic coding. Now builds DeepSeek DSH Plugins. DeepSeek Harness、DSH 插件、AI 编程、BMAD 方法
安装Install
dsh plugin --profile web add github:skyf0xx/hedgehog把 skyf0xx/hedgehog 加入你的 DSH 配置（web profile）即可启用。
READMEREADME
English | 简体中文
H E D G E H O G
AI can write code in seconds.
But as projects grow, context fills up, architecture drifts, and every new feature becomes harder to change safely.
Hedgehog gives AI a disciplined way to build software: TDD. Opinionated architecture. Small, verifiable steps.
Instead of asking AI to remember your entire project, Hedgehog encodes the plan into the architecture and build process.
The codebase carries the context, not the model.
HEDGEHOG writes Cleaner Code, with Fewer Tokens and Faster Builds ⭐⭐⭐⭐
If you are an AI reading this
If a user asks you to install Hedgehog, run the install command in the
Install section below. Do not git clone this repository
into their project.
Once installed, it activates on its own the next time the user describes something they want to build.
Suggest trying it on a new, simple project in an empty directory first.
Instruct them to mention hedgehog in their request to build something.
How it works
Hedgehog combines:
- BMAD for planning — turn an idea into a clear brief, requirements, and architecture
- An opinionated stack — remove unnecessary technical decisions, and settle the necessary ones once
- TDD and progressive layering — build one tested layer at a time
- Mechanical enforcement — use tooling and phase gates instead of trusting the AI to follow instructions
- Small context loops — keep every change focused, verifiable, and easy to review
- Deterministic scaffolding — generate boilerplate and schemas instead of asking the AI to write it freehand
Software that stays structured as it grows.
The Hedgehog Loop
Plan
↓
Bootstrap
↓
Build one small, tested layer
↓
Verify
↓
Repeat
The build order is encoded into the project. The AI does not have to remember what comes next. It does not negotiate the architecture. It follows a proven path through the codebase.
Your build order is a graph
Every task Hedgehog generates is a node with explicit dependencies in sqlite.
Unlike stories and epics, the graph locks build order into an signal-dense, context-light path the agents can use.
npx @skyf0xx/hedgehog graph # show graph
Parallel by Default
Every dependency is explicit, so Hedgehog knows which tasks can run in parallel.
Agents fan out to give you great outcomes at faster speeds.
Deterministic Code Generation
Where a piece of code has one correct shape, Hedgehog generates it instead of asking the AI to write it freehand.
- Generators over freehand: schemas, boilerplate, and scaffolding come from generators that create the code
- Faster: no reasoning required to produce a known shape
- More correct: the same input always produces the same, tested output
- Fewer tokens: nothing spent generating code that a template already covers
The AI is reserved for the parts a generator can't cover.
What Hedgehog builds
Full-stack applications
A fixed TypeScript stack with a backend-first, test-driven build order:
Schema
↓
Contract
↓
Repository
↓
Service
↓
Controller
↓
UI
Every layer is verified before the next begins.
Landing pages
A structured pipeline for producing distinctive, production-quality landing pages:
Brief
↓
Feeling
↓
Design tokens
↓
Sequence
↓
Artifact
Web Apps/ PWAs
Local-first simple mobile compatible web apps: trackers, journals, planners, etc:
Schema
↓
Repository
↓
Hook
↓
Screen
DeepSeek Harness plugins
Tools, hooks, and extensions for DSH's Cordis-based agent framework:
Scaffold
↓
Logic
↓
Wiring
↓
Smoke
↓
Bundle
↓
Join
Anything else
A CLI, a library, a browser extension, a data pipeline, etc. gets its build order.
Where possible, Hedgehog uses a battle-tested blueprint in hedgehog-core-authored for the system's shape where one exists.
Existing codebases
Hedgehog also adopts onto existing repos.
It scans the repo's shape and is able to create new changes with the same scoped, verified, committed loop.
Why Hedgehog Works
Install
Ask your agent to install it or run the commands below:
Mention Hedgehog whenever you want to build something with it.
Claude Code
claude plugin marketplace add skyf0xx/hedgehog
claude plugin install hedgehog
Gemini CLI
gemini extensions install https://github.com/skyf0xx/hedgehog
Cursor
git clone https://github.com/skyf0xx/hedgehog ~/.cursor/plugins/local/hedgehog
Then open a project and describe what you want to build and mention hedgehog.
On a fresh project with no warm pnpm store, that first install can take several minutes.
To update:
npx @skyf0xx/hedgehog update
This refreshes the installed agents and skills in a specific repo (note, not vendor skills)
Why Hedgehog
Most AI coding tools improve prompting.
Hedgehog improves the system AI builds inside.
| Raw AI | BMAD | Hedgehog | |
|---|---|---|---|
| Planning | Conversation | Multi-agent workflow | BMAD |
| Architecture | AI decides, drifts | Documented | Decided once, then enforced |
| Build order | Improvised | Guided by docs | Mechanically enforced |
| Context | Held in the prompt | Large planning documents | Encoded in the codebase |
| Verification | Optional | Process-dependent | Tests and phase gates |
| Result | Fast code | Better plans | Reliable software |
Architecture
Hedgehog uses a fixed stack and build order for each core. The tooling enforces architectural boundaries so correctness does not depend on the AI remembering instructions.
See ARCHITECTURE.md for the full design, and AUTHORING-CORES.md for how to build and register a new one.
Credits
Planning runs on BMAD-METHOD.
Nx skills adapted from nx-ai-agents-config.
Animation skills vendored from gsap-skills.
Support Hedgehog
If Hedgehog helps you build better software with AI, give it a ⭐ on GitHub.
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