vibe-coding-ai-rules python.instructions.md

A set of Python coding rules covering type hints, data validation, asynchronous input and output, code style, and error handling. Python is a programming language commonly used for web services, automation, and data work.

In plain words
What is it for?
Add typed function signatures, validate data with Pydantic, run I/O asynchronously, use modern Python structures and pathlib, and define specific exceptions.
Why use it?
It provides consistent patterns for writing clearer Python code and handling invalid data and failures explicitly.

Instructions file for GitHub Copilot

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/obviousworks/vibe-coding-ai-rules/python
Clone the repo
git clone --depth 1 https://github.com/obviousworks/vibe-coding-ai-rules

Made for: GitHub Copilot.

Per session 164 This file is loaded in full into every session.
When invoked 164 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00164 $0.00164
Opus 5 $0.00082 $0.00082
Sonnet 5 $0.00033 $0.00033
Haiku 4.5 $0.00016 $0.00016

Measured yesterday against content hash 2a4c06f376c6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

vibe-coding-ai-rules python.instructions.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

ide-specific/github-copilot/.github/instructions/python.instructions.md · 27 lines

What it actually says

Python Patterns

Type Hints

  • Required for all function signatures (params + return type)
  • Use Pydantic models for data validation
  • Use TypeVar and Generic for reusable types

Async

  • Use async/await for all I/O operations
  • Use asyncio.gather() for concurrent operations
  • Never mix sync and async code in hot paths

Style

  • Follow PEP 8 strictly
  • Use structural pattern matching (Python 3.10+) over complex if/else
  • Prefer dataclasses or Pydantic over plain dicts
  • Use pathlib over os.path

Error Handling

  • Use specific exception types (never bare except)
  • Create custom exceptions for domain errors
  • Use contextlib for resource management
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 27 lines · 164 tokens per session scan A 2a4c06f376c6

Subscribe to this mod's changes

vibe-coding-ai-rules python.instructions.md is an instructions file published in the GitHub repository obviousworks/vibe-coding-ai-rules (88 stars, last pushed 2mo ago), licensed MIT. It adds 164 tokens to every session, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other instructions, from other repositories