generate-instructions

Analyze a directory and generate consolidated Cursor rules.

16 stars

Best use case

generate-instructions is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Analyze a directory and generate consolidated Cursor rules.

Teams using generate-instructions should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/generate-instructions/SKILL.md --create-dirs "https://raw.githubusercontent.com/diegosouzapw/awesome-omni-skill/main/skills/development/generate-instructions/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/generate-instructions/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How generate-instructions Compares

Feature / Agentgenerate-instructionsStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Analyze a directory and generate consolidated Cursor rules.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Generate Directory Instructions

Analyze a specific directory in the monorepo and create a consolidated rule file for Cursor.

## Inputs

1. **Target Directory** (required) - The directory path to analyze (e.g., `packages/api`, `apps/web`)

## Output

Create a single file at `.cursor/rules/{DIR_NAME}.mdc` with:

- Frontmatter: `globs: "{DIR_PATH}/**"`
- All 7 sections populated with directory-specific information

## Steps

1. **Analyze the Directory** - Examine code structure, patterns, and conventions
2. **Generate Instructions File** - Create the consolidated file with all sections
3. **Validate Content** - Ensure all mentioned code/patterns actually exist
4. **Review Formatting** - Follow the guidelines below

## Sections to Include

### 1. Overview

- What this directory/package does
- Key concepts and domain terms
- Primary consumers/users of this code
- Integration points with other parts of the monorepo

### 2. Architecture & Patterns

- Folder structure within this directory
- Module boundaries and responsibilities
- Communication patterns (events, APIs, shared state)
- External service integrations

### 3. Stack Best Practices

- Language-specific idioms used here
- Framework patterns and conventions
- Dependency injection approach
- Error handling and validation patterns

### 4. Anti-Patterns

- Patterns to avoid in this directory
- Common mistakes to watch for
- Security pitfalls specific to this code

### 5. Data Models

- Key entities and their relationships
- DTOs and value objects
- Validation rules
- Database/storage patterns

### 6. Security & Configuration

- Environment variables used
- Secrets and sensitive data handling
- Authentication/authorization patterns
- API security considerations

### 7. Commands & Scripts

- Build commands for this directory
- Test commands
- Development scripts
- Deployment commands

## Guidelines

- Each section should be **concise** (aim for 5-10 bullet points per section)
- Use bullet points, not paragraphs
- Include specific file paths and code examples from THIS directory
- Only document patterns that actually exist in the code
- Skip sections that don't apply (but include the header with "N/A" note)
- The `globs` glob should match the target directory (e.g., `packages/api/**`)

## Output Format

```markdown
---
globs: "{DIR_PATH}/**"
---

# {DIR_NAME} Instructions

## Overview
- [specific bullet points]

## Architecture & Patterns
- [specific bullet points]

## Stack Best Practices
- [specific bullet points]

## Anti-Patterns
- [specific bullet points]

## Data Models
- [specific bullet points]

## Security & Configuration
- [specific bullet points]

## Commands & Scripts
- [specific bullet points]
```

Related Skills

generate-status-report

16
from diegosouzapw/awesome-omni-skill

Comprehensive system status report with services, infrastructure, performance metrics, and recommendations

generate-qr-code-natively

16
from diegosouzapw/awesome-omni-skill

Generate QR codes locally without external APIs using native CLI and runtime libraries in Bash and Node.js.

generate-knowledge-base

16
from diegosouzapw/awesome-omni-skill

Generate a product knowledge base from a codebase. Analyzes source code to create an Obsidian vault with architecture docs, API references, domain logic, data models, and infrastructure documentation. Use when the user asks to document a codebase, create a knowledge base, or generate product docs.

e2e-generate

16
from diegosouzapw/awesome-omni-skill

Generate end-to-end tests with Playwright browser automation

Dictation Instructions

16
from diegosouzapw/awesome-omni-skill

Instructions for fixing speech-to-text errors and improving text quality in gh-aw documentation and workflows

copilot-instructions-blueprint-generator

16
from diegosouzapw/awesome-omni-skill

Technology-agnostic blueprint generator for creating comprehensive copilot-instructions.md files that guide GitHub Copilot to produce code consistent with project standards, architecture patterns, and exact technology versions by analyzing existing codebase patterns and avoiding assumptions.

config-generate

16
from diegosouzapw/awesome-omni-skill

Generate configuration files for development tools

api-test-generate

16
from diegosouzapw/awesome-omni-skill

Auto-generate comprehensive API tests for REST and GraphQL endpoints with request/response validation

root-level-project-instructions

16
from diegosouzapw/awesome-omni-skill

Root level project guidelines and initial steps to start and implement EEG processor

generate_quiz_batch

16
from diegosouzapw/awesome-omni-skill

Generates batches of high quality quizzes in JSON format for the BlindsidedGames pool, categorised and rated by difficulty.

weekly-email-team-instructions

16
from diegosouzapw/awesome-omni-skill

Generates The Edmund Bogen Team's weekly market intelligence package: email, article page, dashboard, and community listings pages. Guides team through data collection, validates consistency, and produces all HTML assets ready for deployment to Constant Contact and GitHub.

generate-llms

16
from diegosouzapw/awesome-omni-skill

Generate llms.txt and llms-full.txt files for AI agent consumption following the llmstxt.org standard. Use when updating site content that should be reflected in the llms files, or when building/deploying the site.