Z
z-astral/PCC
PCC (Pretty and Clean Codes) — Principal OOP AI Engineering Skill
View on GitHub ↗Link checked 2026-11-12 · HTTP 200 · opens the vendor's own site
Install & config
Client config (built from the install command this repo gives)
{
"mcpServers": {
"z-astral-pcc": {
"command": "npx",
"args": ["pretty-and-clean-codes"]
}
}
}Parsed from the README we fetched on 2026-11-05; we have not executed it.
command/args come from the install command the repository states. When it is ambiguous, the project README wins.
VS Code (.vscode/mcp.json - the key is servers)
{
"servers": {
"z-astral-pcc": {
"command": "npx",
"args": ["pretty-and-clean-codes"]
}
}
}Same server, but VS Code keeps it under <code>servers</code>.
Claude Code (command line)
claude mcp add --transport stdio z-astral-pcc -- npx pretty-and-clean-codes
Claude Code does not read a config file; add the server with this command.
Key names differ by client: Clients & CLI
- Star count
- 1 ★ · z-astral/PCC · read from the GitHub search API · (checked 2026-11-13 20:00:50)
- Source
- read directly from its GitHub page · type: open-source project
- Harvest history
- first seen 2026-11-06 · last seen 2026-11-14 · seen 9× · listed by 1 sources
- Score
- score 103 · 1 ★ · 1 sources · repo
- Install
npx pretty-and-clean-codes
FAQ (answers come from our records)
How do I install it?
The repository provides this install command:
npx pretty-and-clean-codes. It comes from the repository itself; we cannot guarantee it runs as-is in your client.Who is it for?
We filed it under these tags: 开源项目. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
repository
z-astral/PCC;first catalogued 2026-11-06;last seen 2026-11-14。There is no official certification or quality rating here — we record sources and dates only.# Pretty and Clean Codes (PCC)
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
### Principal OOP AI Engineering Skill
High-Density Object-Oriented Programming • Zero Inline Noise • Terse Scope-Proportional Naming • Flat Control Flow
🇬🇧 English •
🇮🇩 Bahasa Indonesia •
🇯🇵 日本語 •
🇨🇳 简体中文 •
🇮🇳 हिन्दी •
🇷🇺 Русский
# 🇬🇧 English Documentation
> [!NOTE]
> What is Pretty and Clean Codes (PCC) in simple terms?
> Think of PCC as a "Senior Engineer Brain Chip" (Instruction Manual) for your AI coding assistant (such as Cursor, Claude Code, Google Antigravity, OpenCode, Devin, Windsurf, or GitHub Copilot). Once installed, your AI stops writing messy, overly long beginner code and starts writing clean, compact, Object-Oriented code like a Principal Software Architect.
## 💡 Why PCC? (Explained for Everyone)
If you have ever asked an AI to write code, you probably noticed three annoying habits:
1. Narrator Comments Everywhere: The AI writes useless comments on almost every line (// initialize variable, // loop through users), making your file look like a beginner's textbook.
2. Essay-Length Variable Names: The AI creates 40-character variable names like temporaryCustomerAuthenticationTokenString instead of clean, industry-standard names like tok or cfg.
3. Spaghetti if/else Pyramids: The AI nests if inside else inside if up to 6 levels deep, scattering loose functions everywhere instead of organizing them into neat Object-Oriented Programming (OOP) classes.
> [!TIP]
> Save 35%–45% of Your AI Token Quota & Speed Up Generation!
> Because PCC eliminates useless inline comments, compresses verbose variable names, and flattens nested blocks, your AI generates nearly half as many output tokens for the exact same functionality. Responses finish almost 2x faster and cost significantly less on paid API tiers.
## 🏛️ The 4 Engineering Pillars
text
┌─────────────────────────────────────────────────────────────────────────┐
│ PRETTY AND CLEAN CODES (PCC) │
├──────────────────┬──────────────────┬──────────────────┬────────────────┤
│ PILLAR I │ PILLAR II │ PILLAR III │ PILLAR IV │
│ Strict OOP │ Zero Inline │ Terse Scope │ Vertical │
│ Encapsulation │ Comments │ Naming │ Compression │
├──────────────────┼──────────────────┼──────────────────┼────────────────┤
│ • Cohesive class │ • 0 // or # in │ • Micro: it, v, │ • Guard clause │
│ architecture │ method bodies │ k, i, acc, fn │ early return │
│ • readonly state │ • 100% signature │ • Local: ctx, │ • No else │
│ • private helper │ Docblocks on │ cfg, req, res, │ after return │
│ isolation │ classes/methods│ buf, tx, err │ • 3-15 LOC max │
└──────────────────┴──────────────────┴──────────────────┴────────────────┘
### 1. Strict Object-Oriented Encapsulation (OOP)
No loose, floating functions. All business logic, state, and helpers are encapsulated inside cohesive classes (AuthSvc, TokenGuard, OrderCalc, PacketBuf) with explicit visibility modifiers (private, protected, public, readonly).
### 2. Zero Inline Comments & 100% Signature Docblocks
Zero (0) comments are allowed inside a function's body. Instead, PCC forces the AI to write a comprehensive, professional Docblock (JSDoc, TSDoc, Javadoc, or Docstring) directly above the class and method signature—documenting what the function does, its @param inputs, and its @returns output.
High-Density Object-Oriented Programming • Zero Inline Noise • Terse Scope-Proportional Naming • Flat Control Flow
🇬🇧 English •
🇮🇩 Bahasa Indonesia •
🇯🇵 日本語 •
🇨🇳 简体中文 •
🇮🇳 हिन्दी •
🇷🇺 Русский
# 🇬🇧 English Documentation
> [!NOTE]
> What is Pretty and Clean Codes (PCC) in simple terms?
> Think of PCC as a "Senior Engineer Brain Chip" (Instruction Manual) for your AI coding assistant (such as Cursor, Claude Code, Google Antigravity, OpenCode, Devin, Windsurf, or GitHub Copilot). Once installed, your AI stops writing messy, overly long beginner code and starts writing clean, compact, Object-Oriented code like a Principal Software Architect.
## 💡 Why PCC? (Explained for Everyone)
If you have ever asked an AI to write code, you probably noticed three annoying habits:
1. Narrator Comments Everywhere: The AI writes useless comments on almost every line (// initialize variable, // loop through users), making your file look like a beginner's textbook.
2. Essay-Length Variable Names: The AI creates 40-character variable names like temporaryCustomerAuthenticationTokenString instead of clean, industry-standard names like tok or cfg.
3. Spaghetti if/else Pyramids: The AI nests if inside else inside if up to 6 levels deep, scattering loose functions everywhere instead of organizing them into neat Object-Oriented Programming (OOP) classes.
> [!TIP]
> Save 35%–45% of Your AI Token Quota & Speed Up Generation!
> Because PCC eliminates useless inline comments, compresses verbose variable names, and flattens nested blocks, your AI generates nearly half as many output tokens for the exact same functionality. Responses finish almost 2x faster and cost significantly less on paid API tiers.
## 🏛️ The 4 Engineering Pillars
text
┌─────────────────────────────────────────────────────────────────────────┐
│ PRETTY AND CLEAN CODES (PCC) │
├──────────────────┬──────────────────┬──────────────────┬────────────────┤
│ PILLAR I │ PILLAR II │ PILLAR III │ PILLAR IV │
│ Strict OOP │ Zero Inline │ Terse Scope │ Vertical │
│ Encapsulation │ Comments │ Naming │ Compression │
├──────────────────┼──────────────────┼──────────────────┼────────────────┤
│ • Cohesive class │ • 0 // or # in │ • Micro: it, v, │ • Guard clause │
│ architecture │ method bodies │ k, i, acc, fn │ early return │
│ • readonly state │ • 100% signature │ • Local: ctx, │ • No else │
│ • private helper │ Docblocks on │ cfg, req, res, │ after return │
│ isolation │ classes/methods│ buf, tx, err │ • 3-15 LOC max │
└──────────────────┴──────────────────┴──────────────────┴────────────────┘
### 1. Strict Object-Oriented Encapsulation (OOP)
No loose, floating functions. All business logic, state, and helpers are encapsulated inside cohesive classes (AuthSvc, TokenGuard, OrderCalc, PacketBuf) with explicit visibility modifiers (private, protected, public, readonly).
### 2. Zero Inline Comments & 100% Signature Docblocks
Zero (0) comments are allowed inside a function's body. Instead, PCC forces the AI to write a comprehensive, professional Docblock (JSDoc, TSDoc, Javadoc, or Docstring) directly above the class and method signature—documenting what the function does, its @param inputs, and its @returns output.
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- github · https://github.com/z-astral/PCC
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