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coding-standards

Enforce naming, function, and error handling standards across programming languages.

Updated May 5, 2026
Search Tags:#code review#anti-patterns#error handling#coding standards#maintainability#naming conventions
One-click install
npx skills add https://github.com/HyperionBurn/searchv1beta --skill coding-standards-hyperionburn
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: coding-standards
Source: https://github.com/HyperionBurn/searchv1beta/tree/main/.github/skills/coding-standards
Command: npx skills add https://github.com/HyperionBurn/searchv1beta --skill coding-standards-hyperionburn

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It solves inconsistent code style and quality drift across teams and languages by providing a canonical, shareable baseline of naming, structure, error handling, and anti-pattern guidance.

Core Features & Use Cases

  • Canonical cross-language reference: Provides a single source of truth for reviewer agents to embed and apply consistently.
  • Naming and style guardrails: Enforces conventions for variables, functions, constants, booleans, and collection naming across languages.
  • Function and error handling constraints: Guides maximum length, parameter limits, complexity targets, early-return patterns, and contextual error messaging.
  • Maintainability anti-patterns: Flags high-risk practices like mutable global state, unawaited promises, magic numbers, god objects, and swallowed errors.

Quick Start

Use the coding-standards skill when you need a rules baseline for reviewing style, naming, and maintainability in a code review or modernization task.

Frequently Asked Questions about coding-standards

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I enforce consistent coding standards across multiple programming languages?▼

A canonical, shareable baseline of naming, structure, error handling, and anti-pattern guidance solves inconsistent code style and quality drift across teams and multi-language repositories by providing a single source of truth.

What anti-patterns should I check for during a cross-language code review?▼

During a code review, flag high-risk maintainability anti-patterns such as mutable global state, unawaited promises, magic numbers, god objects, and swallowed errors to prevent quality drift across repositories.

Can I use automated reviewer workflows to detect naming convention violations in multi-language repositories?▼

Yes, automated reviewer workflows can detect naming convention violations by embedding deterministic cross-language guardrails for variables, functions, constants, booleans, and collections within multi-language repositories.

What are the best practices for function length and error handling in code review?▼

Best practices for function length and error handling involve enforcing maximum length limits, parameter constraints, complexity targets, early-return patterns, and contextual error messaging to guide maintainability.

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