Generate Custom Instructions From Codebase

AI assistants work better with project-specific context. This skill analyzes codebases to generate custom instructions documenting architecture patterns, coding conventions, technology stack, and project-specific knowledge enabling AI assistants to provide contextually appropriate suggestions and maintain codebase consistency.

What Is This?

Overview

Generate Custom Instructions From Codebase examines project code to produce AI assistant instructions. It identifies architecture patterns and design decisions, extracts coding conventions and style preferences, documents technology stack and dependencies, recognizes common patterns and anti-patterns, highlights important files and directories, notes testing approaches and requirements, and formats instructions for AI assistant consumption.

The skill creates instructions helping AI understand project context without repeated explanations. Generated instructions improve suggestion relevance and maintain established patterns across all team members using the assistant, ensuring a consistent development experience regardless of who is working on a given feature or fix.

Who Should Use This

Development teams using AI assistants. Technical leads establishing standards. Senior developers sharing context. Platform teams standardizing projects. Open source maintainers guiding contributors. Teams onboarding AI tools.

Why Use It?

Problems It Solves

AI suggestions ignore project conventions without context. Custom instructions ensure suggestions follow established patterns, such as preferred abstraction layers, naming schemes, or module boundaries specific to your codebase.

Repeated explanations of architecture waste time. Instructions provide persistent context across sessions, eliminating the need to re-explain foundational decisions every time a new conversation begins.

New team members using AI get inconsistent guidance. Instructions align AI suggestions with team standards.

Project-specific patterns are not recognized. Documentation enables AI to suggest appropriate solutions.

Core Highlights

Architecture pattern extraction. Coding convention identification. Technology stack documentation. File structure explanation. Testing pattern recognition. Common operation examples. Anti-pattern warnings. Context-aware guidance generation.

How to Use It?

Basic Usage

Point to codebase or provide project information. The skill analyzes code and generates custom instructions for AI assistants.

Generate custom instructions for this React project
analyzing components and patterns

Create AI instructions documenting our
backend architecture and conventions

Specific Scenarios

For architecture clarity, emphasize patterns.

Generate instructions documenting clean
architecture layers and dependencies

For style consistency, focus on conventions.

Create instructions covering naming,
formatting, and code organization rules

For technology specifics, detail stack.

Generate instructions about our TypeScript,
React, and GraphQL technology choices

Real World Examples

A team uses AI assistant for React development but suggestions violate established patterns. Custom instructions document component structure using hooks not classes, state management with Context API not Redux, styling with CSS modules not inline styles, testing with React Testing Library, and file organization by feature. AI suggestions immediately align with project conventions.

A backend team has specific architecture including CQRS pattern, repository abstraction, and domain events. Generated instructions explain command and query separation, repository interface usage, domain event publishing, and transaction boundaries. AI assistant suggests code following architecture without constant reminders.

An open source project receives contributions using AI that misunderstand project goals. Custom instructions document minimalist philosophy, performance requirements, backwards compatibility needs, testing expectations, and contribution workflow. Contributors using AI assistants generate appropriate code from start reducing review iterations.

Advanced Tips

Update instructions as project evolves. Include anti-pattern warnings with concrete examples of what to avoid and why. Provide example code snippets drawn directly from the existing codebase to ground the instructions in real, proven patterns. Document decision rationale so AI understands not just what the conventions are but the reasoning behind them. Version control instructions alongside source code so changes remain traceable. Share across team. Test with actual AI usage by running representative prompts and verifying output quality. Balance detail with readability.

When to Use It?

Use Cases

Team AI assistant setup. Project context documentation. Code consistency improvement. Onboarding acceleration. AI suggestion quality enhancement. Pattern enforcement. Architecture alignment. Contribution guidance.

Related Topics

AI assistant configuration. Project documentation. Coding standards. Architecture decision records. Code style guides. Development workflows. Context management for AI.

Important Notes

Requirements

Access to codebase. Understanding of architecture. Knowledge of conventions. Clarity about patterns. AI assistant supporting custom instructions.

Usage Recommendations

Generate early in project lifecycle. Review for accuracy. Update regularly, particularly after significant refactors or technology migrations. Share with team. Test effectiveness. Include examples. Document exceptions. Keep concise but complete.

Limitations

Cannot capture all nuances. Requires maintenance. Quality depends on codebase consistency. May miss recent changes. Should supplement not replace documentation.