askill
guid-convention-extraction

guid-convention-extractionSafety --Repository

Extracts naming conventions, code style guidelines, and structural patterns specific to the project. Analyzes variable naming, function signatures, file organization, and comment styles.

2 stars
1.2k downloads
Updated 12/6/2025

Package Files

Loading files...
SKILL.md

Convention Extraction

Pattern Description

What: Identifies and documents recurring conventions and stylistic choices within a project's codebase.

When: Use this skill to understand a project's established coding standards, when onboarding to a new codebase, or when ensuring consistency during development.

Context: Applicable across various programming languages and frameworks, focusing on observable patterns rather than prescriptive rules.

Project-Specific Conventions

Naming Conventions

  • Variables: [e.g., camelCase for JS, snake_case for Python]
  • Functions/Methods: [e.g., verbNoun() for actions]
  • Classes/Interfaces: [e.g., PascalCase]
  • Files: [e.g., componentName.tsx, utility-function.js]

Code Style Guidelines

  • Indentation: [e.g., 2 spaces, 4 spaces, tabs]
  • Brace Style: [e.g., K&R, Allman]
  • Line Length: [e.g., max 80 characters]
  • Comments: [e.g., JSDoc, inline, single-line vs multi-line]

Structural Patterns

  • File Organization: [e.g., src/components, src/utils, lib/]
  • Module Structure: [e.g., barrel files, index.ts exports]
  • Dependency Injection: [e.g., manual, framework-assisted]
  • Error Handling: [e.g., try-catch, custom error classes]
  • Concurrency: [e.g., async/await, threads, goroutines]
  • Logging: [e.g., consistent log levels, structured logging]

Common Pitfalls

❌ Inconsistent Application

Problem: Conventions are documented but not consistently followed. Why It Fails: Leads to code readability issues and developer confusion. Better Approach: Automate linting and formatting where possible; conduct regular code reviews.

❌ Over-Prescription

Problem: Too many rigid rules, stifling developer flexibility. Why It Fails: Can make coding tedious and discourage adoption. Better Approach: Focus on key conventions that impact readability and maintainability.

Convention Analysis for Skill Creation

Identifying Skill Opportunities

When extracting conventions, look for patterns that could benefit from dedicated skills:

  • Recurring Workflows: Repeated processes that could be codified
  • Complex Patterns: Multi-step conventions that require coordination
  • Team-Specific Approaches: Unique solutions different from standard practices
  • Integration Patterns: How different technologies or components work together

Pattern Frequency Assessment

Consider these factors when evaluating convention relevance for skill creation:

  • Usage Frequency: How often do developers encounter this pattern?
  • Complexity Level: Is this simple enough to remember or complex enough to benefit from documentation?
  • Team Impact: Does this affect multiple team members or workflows?
  • Maintenance Needs: Will this pattern evolve or change over time?

Tool Integration Opportunities

Some conventions may suggest specific tool selections:

  • Code Formatting: Linters, formatters, pre-commit hooks
  • Testing Patterns: Specific testing frameworks or assertion libraries
  • Build Processes: Build tools, bundlers, automation scripts
  • Documentation: Documentation generators, template systems

Related Resources

Related Skills

  • universal-technology-discovery: To understand the technologies driving conventions.
  • repository-pattern-recognition: For understanding how conventions relate to repository structure.
  • skill-creation: For creating skills based on extracted conventions and patterns.
  • tool-selection-guidance: For selecting tools that support established conventions.

Related Agents

  • code-reviewer-agent: To enforce extracted conventions.
  • frontend-specialist: For frontend-specific convention guidance.
  • backend-specialist: For backend and API convention patterns.

External Resources

Install

Download ZIP
Requires askill CLI v1.0+

AI Quality Score

AI review pending.

Metadata

Licenseunknown
Version-
Updated12/6/2025
Publisherxilnick

Tags

apici-cdobservability