⚡ Supercharged Dev

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English · 中文

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Your AI coder burns $200/month on junk tokens. This MCP server makes it think first, test first, compress first. 11 tools, one install.

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The Problem

AI coding assistants are great at generating code fast. But:

Without Supercharged Dev	With Supercharged Dev
Jumps straight to code without clarifying what you actually want	Designs first — asks the right questions before writing a single line
Writes production code with no tests, hoping it works	Tests first — RED → GREEN → REFACTOR, every time
Guesses at bug fixes, changes random things, makes it worse	Debugs systematically — finds the root cause before touching anything
Submits PRs with no self-review, wasting your time	Reviews itself — 5-dimension check before showing you the diff
Burns tokens on verbose JSON, logs, and boilerplate	Compresses — saves 60–95% of tokens before they reach the LLM

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What You Get (In One Picture)

You: "Add a login page"
      │
      ▼
AI calls brainstorm_design ──→ "Who are the users? What auth method?
                                What happens on failure? Let me propose 2 approaches..."
      │ (you approve the design)
      ▼
AI calls decompose_task ──→ Task 1: Create src/auth/login.tsx
                             Task 2: Add src/auth/__tests__/login.test.tsx
                             Task 3: Wire up route in app.tsx
                             (each task: 2-5 min, verifiable)
      │
      ▼
AI calls generate_test_skeleton ──→ "Here's a failing test for the login component.
                                     Run it first — it should fail. Then I'll implement."
      │ (test fails ✓)
      ▼
AI implements, then calls review_code_diff ──→ "Self-review:
                                                 ✓ Plan Compliance
                                                 ✓ Correctness
                                                 ⚠ Edge Cases — missing empty password case"
      │ (fixes the edge case)
      ▼
You get tested, reviewed, production-ready code.

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When Do You Actually Use Each Tool?

Scenario	Tool to call	What happens
"I want to add a feature but I'm not sure about the approach"	brainstorm_design	Walks you through clarifying questions, proposes 2–3 approaches with tradeoffs
"I have a design doc, now make a plan"	decompose_task	Breaks it into 2–5 minute tasks. Each has a file path, code, and verification step
"Just wrote a bunch of code, is it any good?"	review_code_diff	5-dimension review. Critical issues block progress.
"Something's broken and I have no idea why"	debug_root_cause	4-phase process. Won't let you fix anything until you've proven the root cause.
"I need to write tests for this"	generate_test_skeleton	RED → GREEN → REFACTOR workflow. Test first, code second.
"This API response is 10,000 lines of JSON"	compress_content	Compresses to ~2,000 tokens. Same answer quality. Saves money.
"How much have I saved so far?"	compression_stats	Shows total tokens, savings %, cache hit rate, session runtime.
"What skills are available?"	list_skills	Shows all 13 Superpowers skills with descriptions and trigger conditions.

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11 MCP Tools

🧠 Workflow (5 tools)

Tool	What it does
brainstorm_design	Socratic design exploration. Refuses to code until you've approved an approach.
decompose_task	Design spec → 2–5 min executable sub-tasks with file paths and verification steps.
review_code_diff	Self-review across 5 dimensions: Plan Compliance, Correctness, Testing, Edge Cases, Style.
debug_root_cause	4-phase debugging. Gate at each phase. No fixes until root cause is proven.
generate_test_skeleton	RED → GREEN → REFACTOR. Generates a failing test before you write any production code.

📖 Knowledge (3 tools)

Tool	What it does
get_skill	Returns the full Markdown of any Superpowers skill — injectable into any AI instruction.
list_skills	Lists all 13 available skills with descriptions. Discover what's possible.
get_preset_info	Shows what's in each preset (minimal/default/aggressive).

🔧 Compression (3 tools)

Tool	What it does	Typical savings
compress_content	Compresses content (Headroom or fallback). Auto-detects JSON/code/text.	50–92%
retrieve_original	Pulls original content back from LRU cache if the LLM needs it.	—
compression_stats	Live stats: total requests, tokens saved, cache hit rate, engine, uptime.	—

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Skills Library (13 Skills)

#	Skill	Automatically triggers when...
1	brainstorming	You ask for any new feature or behavior change
2	writing-plans	A design has been approved
3	subagent-driven-development	Tasks need independent, isolated execution
4	executing-plans	You want batch execution with checkpoints
5	test-driven-development	Any production code is about to be written
6	systematic-debugging	A bug is reported
7	verification-before-completion	Someone claims a fix is done
8	requesting-code-review	A task is marked complete
9	receiving-code-review	Review feedback is received
10	using-git-worktrees	Code is about to be written in an existing project
11	finishing-a-development-branch	All tasks on a branch are done
12	dispatching-parallel-agents	Multiple independent modules need work
13	writing-skills	A new skill needs to be created

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Who Is This For?

• Solo developers who want the discipline of a senior engineering team in their AI assistant
• Teams who want consistent code quality across AI-generated contributions
• Anyone tired of $200+ Claude bills — compression pays for itself in a day
• MCP power users who want one server that covers the full dev workflow
• AI coding skeptics — add guardrails so the AI doesn't run wild

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Quick Start

# 1. Install
pip install supercharged-dev

# 2. Start the MCP server
supercharged mcp serve

# 3. Print the config for your client
supercharged mcp config

Claude Desktop

{
  "mcpServers": {
    "supercharged": {
      "command": "uvx",
      "args": ["supercharged-dev", "mcp", "serve"]
    }
  }
}

Project Setup (Copies skill files + generates config)

cd your-project
supercharged init --preset aggressive

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Presets

Preset	Skills	Compression	For
minimal	3	❌	Just the essentials: brainstorm, TDD, review
default	9	❌	Full workflow minus advanced features
aggressive	13	✅	Everything. Maximum discipline, minimum spend.

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Compression (Optional Dependency)

pip install supercharged-dev[compress]

Content type	Typical savings
JSON API responses / MCP tool output	70–86%
Code search results (100 hits)	92%
Server logs	90%+
Full agent sessions (10+ tool calls)	85%

No quality loss — compressed content produces the same answers (verified on GSM8K, TruthfulQA, SQuAD).

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中文说明

这是什么？

一个 MCP Server，让你的 AI 编程助手学会先思考再写代码、先测试再上线、先压缩再花钱。

它解决的问题：

没装之前	装了之后
AI 上来就写代码，不管你到底想要什么	先用苏格拉底式提问理清设计，批准后才动工
没有测试的保护，代码靠"祈祷"	TDD 铁律：RED → GREEN → REFACTOR
Debug 靠猜，改来改去越改越糟	系统化四阶段调试，找到根因前禁止修复
提 PR 不审查，浪费你时间	5 维度自审查，Critical 问题阻塞进度
JSON/日志/模板白白烧 Token	压缩 60–95%，答案质量不变，账单大幅下降

典型用法

当你想...	调用这个工具	会发生什么
加功能但不确定怎么做	brainstorm_design	挨个提问帮你理清需求，提 2–3 个方案让你选
把设计方案落地	decompose_task	拆成 2–5 分钟的小任务，每个都有文件路径和验证步骤
刚写的代码质量怎么样	review_code_diff	5 个维度逐一审查，Critical 问题会阻止继续
出 bug 了不知道原因	debug_root_cause	四阶段流程，不找到根因不准修复
需要写测试	generate_test_skeleton	先生成会失败的测试，然后写最少代码让它通过
API 返回了一万行 JSON	compress_content	压到 ~2000 token，省 70–86%，答案质量不变
想看省了多少钱	compression_stats	实时统计：总请求、Token 节省、缓存命中率

11 个 MCP 工具

类别	工具	一句话
🧠 工作流	brainstorm_design	写代码前先想清楚
🧠 工作流	decompose_task	设计 → 可执行任务
🧠 工作流	review_code_diff	5 维度自我审查
🧠 工作流	debug_root_cause	根因不明不修复
🧠 工作流	generate_test_skeleton	先写失败的测试
📖 知识	get_skill	读取任意 skill 文档
📖 知识	list_skills	列出全部 13 个 skill
📖 知识	get_preset_info	查看预设配置
🔧 压缩	compress_content	压缩省 Token
🔧 压缩	retrieve_original	从缓存取回原文
🔧 压缩	compression_stats	省钱统计

适合谁用？

• 独立开发者 — 一个人也有团队的工程纪律
• 团队 — 保证 AI 生成的代码质量一致
• 心疼账单的人 — 压缩省的钱可能比工具本身贵得多
• MCP 重度用户 — 一个 Server 覆盖完整开发流程
• 对 AI 编程有顾虑的人 — 加上护栏，不让 AI 放飞自我

快速开始

pip install supercharged-dev
supercharged mcp serve

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License

MIT · Built on Superpowers and Headroom.