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mrgoonie AI Skills

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Explorez les skills IA publiés de mrgoonie et consultez leurs instructions source.

Statistiques de l’auteur

Skills indexés

34

Étoiles des dépôts des skills indexés

56,906

Forks du dépôt

11,884

Moyenne des étoiles par skill indexé

1,674

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

34 skills

Explorer

GitHub

systematic-debugging

mrgoonie

Four-phase debugging framework that ensures root cause investigation before attempting fixes. Never jump to solutions.

GitHub

chrome-devtools

mrgoonie

Browser automation, debugging, and performance analysis using Puppeteer CLI scripts. Use for automating browsers, taking screenshots, analyzing performance, monitoring network traffic, web scraping, form automa...

GitHub

devops

mrgoonie

Deploy to Cloudflare (Workers, R2, D1), Docker, GCP (Cloud Run, GKE), Kubernetes (kubectl, Helm). Use for serverless, containers, CI/CD, GitOps, security audit.

GitHub

inversion-exercise

mrgoonie

Flip core assumptions to reveal hidden constraints and alternative approaches - "what if the opposite were true?"

GitHub

context-engineering

mrgoonie

Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evalu...

GitHub

docs-seeker

mrgoonie

Searching internet for technical documentation using llms.txt standard, GitHub repositories via Repomix, and parallel exploration. Use when user needs: (1) Latest documentation for libraries/frameworks, (2) Doc...

GitHub

aesthetic

mrgoonie

Create aesthetically beautiful interfaces following proven design principles. Use when building UI/UX, analyzing designs from inspiration sites, generating design images with ai-multimodal, implementing visual...

GitHub

problem-solving

mrgoonie

Creative problem-solving techniques for breaking through stuck points - includes collision-zone thinking, inversion, pattern recognition, and simplification

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.