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majesticlabs-dev AI Skills

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Explorez les skills IA publiés de majesticlabs-dev et consultez leurs instructions source.

Statistiques de l’auteur

Skills indexés

200

Étoiles des dépôts des skills indexés

4,009

Forks du dépôt

602

Moyenne des étoiles par skill indexé

20

Les étoiles d’un dépôt peuvent se répéter entre ses skills.

200 skills

Explorer

GitHub

solid-queue-coder

majesticlabs-dev

Use when configuring or working with Solid Queue for background jobs. Applies Rails 8 conventions, database-backed job processing, concurrency settings, recurring jobs, and production deployment patterns.

GitHub

proposal-writer

majesticlabs-dev

Templates and frameworks for creating winning sales proposals. Executive summaries, scope of work, pricing strategies, and closing elements.

GitHub

first-principles

majesticlabs-dev

Apply first-principles thinking to break down complex problems into fundamental truths and rebuild solutions from the ground up. Use when solving strategic decisions, breaking through blockers, or challenging a...

GitHub

etl-core-patterns

majesticlabs-dev

Core ETL reliability patterns including idempotency, checkpointing, error handling, chunking, retry logic, and logging.

GitHub

llms-txt-builder

majesticlabs-dev

Create llms.txt files that help AI systems navigate and understand your site structure for better citations.

GitHub

rspec-coder

majesticlabs-dev

This skill guides writing comprehensive RSpec tests for Ruby and Rails applications. Use when creating spec files, writing test cases, or testing new features. Covers RSpec syntax, describe/context organization...

GitHub

keyword-research

majesticlabs-dev

Strategic content planning without expensive tools. 6 Circles Method to find what to write about and prioritize it.

GitHub

rails-debugger

majesticlabs-dev

Use proactively when encountering Rails errors, test failures, build issues, or unexpected behavior. Analyzes errors, reproduces issues, and identifies root causes.

GitHub

referral-program

majesticlabs-dev

Design viral referral programs with incentive structures, sharing mechanics, tracking systems, and optimization strategies to turn customers into advocates who drive new customer acquisition.

GitHub

action-policy-coder

majesticlabs-dev

Use proactively for authorization with ActionPolicy. Creates policies, scopes, and integrates with GraphQL/ActionCable. Preferred over Pundit for composable, cacheable authorization.

GitHub

readme-craft

majesticlabs-dev

Production-grade README.md patterns for any project type. Use when creating project documentation, writing README files, or improving existing docs. Covers hero sections, quick start examples, comparison tables...

GitHub

gem-builder

majesticlabs-dev

Comprehensive guide for building production-quality Ruby gems. Use when creating new gems, structuring gem architecture, implementing configuration patterns, setting up testing, or preparing for publishing. Cov...

GitHub

document-review

majesticlabs-dev

Review legal documents as an experienced attorney. Analyzes contracts, ToS, privacy policies, NDAs, and corporate docs section-by-section. Identifies risks, gaps, and unfavorable terms with specific replacement...

GitHub

help-docs-writer

majesticlabs-dev

Create customer-facing help documentation for product features. Analyzes codebase to extract feature details, transforms into user-friendly walkthroughs with troubleshooting sections.

GitHub

sql-patterns

majesticlabs-dev

Advanced SQL patterns including window functions, CTEs, recursive queries, and optimization techniques.

GitHub

retention-system

majesticlabs-dev

Design comprehensive customer retention systems with health scoring, churn prediction, proactive engagement workflows, and customer success frameworks to maximize lifetime value.

GitHub

frontend-design-philosophy

majesticlabs-dev

Design thinking principles for distinctive interfaces. Covers aesthetic direction, anti-patterns, and avoiding generic AI-generated aesthetics.

GitHub

slogan-generator

majesticlabs-dev

Generate and evaluate marketing slogans for any product or service. Creates options across multiple angles, scores against criteria, and recommends the best fit.

Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.