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Skills IA devops llm ai

Découvrez les skills devops llm ai, comparez leurs dépôts et consultez leurs instructions.

Catégories: devops llm ai

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GitHub

dhh-coder

majesticlabs-dev

Write Ruby and Rails code in DHH's distinctive 37signals style. Use this skill when writing Ruby code, Rails applications, creating models, controllers, or any Ruby file. Triggers on Ruby/Rails code generation,...

GitHub

language

majesticlabs-dev

Research and use customer language across Product and Marketing. Sales Safari methodology for finding watering holes, extracting pain language, and creating "OH YEAH!" resonance.

GitHub

content-optimizer

majesticlabs-dev

Content optimization workflow covering keyword integration, semantic enhancement, structure optimization, and AI extractability. Use for improving existing content for both search engines and LLMs.

GitHub

marketing-strategy

majesticlabs-dev

Build a custom marketing strategy through an interactive interview. Develops business positioning, audience targeting, channel selection, and customer journey—then exports as a reusable JSON profile.

GitHub

hierarchical-agents

majesticlabs-dev

Generate hierarchical AGENTS.md structure for codebases to optimize AI agent token usage. Use when creating AGENTS.md files, documenting codebase structure, setting up agent guidance, organizing project documen...

GitHub

fluff-detector

majesticlabs-dev

Detect human-oriented content in LLM artifacts. Flags attribution, personas, redundant explanations, marketing language, and decorative elements that waste tokens without improving LLM behavior.

GitHub

research-compound

majesticlabs-dev

Automatically check and update folder-specific AGENTS.md during research. Before investigating a domain, read nearest AGENTS.md for existing context. After discovering valuable patterns, append learnings to tha...

GitHub

brand-voice

majesticlabs-dev

Codify your brand's writing style into a reusable voice guide. Analyzes existing content to extract patterns, then generates a comprehensive style document for consistent messaging across all channels.

GitHub

sales-messaging

majesticlabs-dev

Build sales messaging frameworks with value propositions, persona-specific talk tracks, and objection handling matrices.

GitHub

free-tool-arsenal

majesticlabs-dev

Build a complete business tech stack with 100% free tools. Find powerful zero-cost alternatives, automation workflows, and workarounds for free plan limitations.

GitHub

case-study-writer

majesticlabs-dev

Create compelling customer case studies for marketing. Guides through information gathering and produces polished case study documents.

GitHub

buyer-journey-mapper

majesticlabs-dev

Create persona × journey grids for AEO (Answer Engine Optimization) content strategy. Maps specific questions to buyer stages for AI citation optimization.

GitHub

agent-sdk

majesticlabs-dev

Guide for Claude Agent SDK - build custom AI agents powered by Claude. Covers installation, authentication providers, tool permissions, file-based configuration, TypeScript/Python code examples, and project sca...

GitHub

skill-design-philosophy

majesticlabs-dev

Core philosophy for designing Claude Code skills - when to use skills vs agents, the knowledge test, and what makes skills valuable. Use when deciding component type or evaluating skill quality.

GitHub

power-words

majesticlabs-dev

Enhance copy with emotional trigger words from 21 psychological categories. Transform bland text into compelling, conversion-focused content.

GitHub

customer-discovery

majesticlabs-dev

Find where potential customers discuss problems online and extract their language patterns. Provides starting points for community research, not exhaustive coverage.

GitHub

llms-txt-builder

majesticlabs-dev

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

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.

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.

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