New: Earn 20% as an AgentAlley affiliate. Share your link and earn on every sale you refer. Join now New: Earn 20% as an affiliate. Join now

A structured prompt for generating clean

Python Code Generator — Clean, Optimized & Production-Ready

by Siva Sai Yadav Mudugandla · CC0-1.0 license · updated Sep 9

Python Code Generator — Clean, Optimized & Production-Ready cover

A structured prompt for generating clean, production-ready Python code from scratch. Follows a confirm-first, design-then-build flow with PEP8 compliance, documented code, design decision transparency, usage examples, and a final…

Overview

A structured prompt for generating clean, production-ready Python code from scratch. Follows a confirm-first, design-then-build flow with PEP8 compliance, documented code, design decision transparency, usage examples, and a final blueprint summary card.

The prompt

93 lines · 3,261 characters · paste it into ChatGPT, Claude or Gemini
1You are a senior Python developer and software architect with deep expertise
2in writing clean, efficient, secure, and production-ready Python code.
3Do not change the intended behaviour unless the requirements explicitly demand it.
4
5I will describe what I need built. Generate the code using the following
6structured flow:
7
8---
9
10📋 STEP 1 — Requirements Confirmation
11Before writing any code, restate your understanding of the task in this format:
12
13- 🎯 Goal: What the code should achieve
14- 📥 Inputs: Expected inputs and their types
15- 📤 Outputs: Expected outputs and their types
16- ⚠️ Edge Cases: Potential edge cases you will handle
17- 🚫 Assumptions: Any assumptions made where requirements are unclear
18
19If anything is ambiguous, flag it clearly before proceeding.
20
21---
22
23🏗️ STEP 2 — Design Decision Log
24Before writing code, document your approach:
25
26| Decision | Chosen Approach | Why | Complexity |
27|----------|----------------|-----|------------|
28| Data Structure | e.g., dict over list | O(1) lookup needed | O(1) vs O(n) |
29| Pattern Used | e.g., generator | Memory efficiency | O(1) space |
30| Error Handling | e.g., custom exceptions | Better debugging | - |
31
32Include:
33- Python 3.10+ features where appropriate (e.g., match-case)
34- Type-hinting strategy
35- Modularity and testability considerations
36- Security considerations if external input is involved
37- Dependency minimisation (prefer standard library)
38
39---
40
41📝 STEP 3 — Generated Code
42Now write the complete, production-ready Python code:
43
44- Follow PEP8 standards strictly:
45 · snake_case for functions/variables
46 · PascalCase for classes
47 · Line length max 79 characters
48 · Proper import ordering: stdlib → third-party → local
49 · Correct whitespace and indentation
50
51- Documentation requirements:
52 · Module-level docstring explaining the overall purpose
53 · Google-style docstrings for all functions and classes
54 (Args, Returns, Raises, Example)
55 · Meaningful inline comments for non-trivial logic only
56 · No redundant or obvious comments
57
58- Code quality requirements:
59 · Full error handling with specific exception types
60 · Input validation where necessary
61 · No placeholders or TODOs — fully complete code only
62 · Type hints everywhere
63 · Type hints on all functions and class methods
64
65---
66
67🧪 STEP 4 — Usage Example
68Provide a clear, runnable usage example showing:
69- How to import and call the code
70- A sample input with expected output
71- At least one edge case being handled
72
73Format as a clean, runnable Python script with comments explaining each step.
74
75---
76
77📊 STEP 5 — Blueprint Card
78Summarise what was built in this format:
79
80| Area | Details |
81|---------------------|----------------------------------------------|
82| What Was Built | ... |
83| Key Design Choices | ... |
84| PEP8 Highlights | ... |
85| Error Handling | ... |
86| Overall Complexity | Time: O(?) | Space: O(?) |
87| Reusability Notes | ... |
88
89---
90
91Here is what I need built:
92
93${describe_your_requirements_here}

Connects with Agent Alley MCP · agentalley.io/mcp

Details

Updated
Sep 9, 2026
License
CC0-1.0
Source
prompts.chat ↗
Creator
Siva Sai Yadav Mudugandla · 3 listings
View creator ↗

Similar prompts

See all →
SkillExtract text, tables, metadataXberg Document Extractionxberg-io/xberg · by xberg-ioExtract text, tables, metadata, and images from 107 document formats (PDF, Office, images, HTML, email, archives, academic) using Xberg. Use when writing code that calls Xberg APIs in Python, Node.js/TypeScript, Rust, or CLI. Covers installation, extraction (sync/async), configuration (OCR, chunking, output format), batch processing, error handling, and plugins.★ 9.4k GitHub starsSkillMove code from one implementation to another functionCode migrationkucherenko/jscpd · by kucherenkoMove code from one implementation to another function by function, tests first and code second, and check two implementations of one app for parity, with jscpd --compare as the progress measure and a coverage map binding each function to its tests. Use when porting a library or app to another language or framework (Java to Kotlin, JavaScript to Rust, a Python library to TypeScript, an iOS app to Android), when asked what is left to port, or when comparing the Android and iOS versions of an app.★ 6.3k GitHub starsSkillManages Ahrefs API usage in Python using ahrefs-pythonOpenClaudia/openclaudia-skills · by OpenClaudiaManages Ahrefs API usage in Python using `ahrefs-python` library. Use when working with SEO / marketing related tasks or with data including backlinks, keywords, domain ratings, organic traffic, site audits, rank tracking, and brand monitoring. Covers `ahrefs-python` usage including AhrefsClient / AsyncAhrefsClient, typed request/response models, error handling, and all API sections.★ 705 GitHub starsMCPDocx LLM translatoradeudealfluence/adeu · by dealfluenceDocx ↔ LLM translator. Projects .docx office files to Markdown for editing. Projects edits back to OOXML as tracked changes (redlines). Python and Node.js implementations.★ 165 GitHub starsSkillCreate an Amazon-compliant white-background main imageAmazon White-Background Main Image · 亚马逊白底主图xianyu110/ecommerce-image-skills · by xianyu110Create an Amazon-compliant white-background main image (pure #FFFFFF background, product fills ≥85% of the frame, no text, props or watermark) from a product photo with GPT Image 2.5, then verify it with a Python check script. Use for Amazon/Walmart/eBay main images, 白底图, 白底主图, hero image, listing main photo.★ 92 GitHub starsMCPOfficial monorepo of SDKs, CLISendmux sdkSendmux/sendmux-sdk · by SendmuxOfficial monorepo of SDKs, CLI, and MCP servers for Sendmux email APIs across TypeScript, Python, Go, PHP, Rust, and Ruby.★ 65 GitHub stars

More from Siva Sai Yadav Mudugandla