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Skills IA devops llm ai

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

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GitHub

gemini-extension-development

melodic-software

Expert guide for building and managing Gemini CLI Extensions. Covers extension anatomy, GEMINI.md context, commands, MCP integration, and publishing. Use when creating Gemini extensions, linking local extension...

GitHub

command-development

melodic-software

Central authority for Claude Code slash commands. Covers built-in commands, custom slash commands (project and personal), plugin commands, MCP slash commands, Skill tool (unified for commands and skills), front...

GitHub

rag-architecture

melodic-software

Retrieval-Augmented Generation (RAG) system design patterns, chunking strategies, embedding models, retrieval techniques, and context assembly. Use when designing RAG pipelines, improving retrieval quality, or...

GitHub

reduce-delegate-framework

melodic-software

Apply R&D framework to optimize prompts and context. Use when optimizing context window usage, reducing prompt size, delegating to specialized agents, or applying systematic context management.

GitHub

elicitation-methodology

melodic-software

Hub skill for requirements elicitation. Provides technique selection, orchestration guidance, LLMREI patterns, and autonomy level configuration. Use when gathering requirements from stakeholders, conducting eli...

GitHub

ml-inference-optimization

melodic-software

ML inference latency optimization, model compression, distillation, caching strategies, and edge deployment patterns. Use when optimizing inference performance, reducing model size, or deploying ML at the edge.

GitHub

product-expert-design

melodic-software

Design user-facing agent experts for adaptive UX and personalization. Use when building product features that learn from user behavior, creating per-user expertise files, or implementing AI-driven personalizati...

GitHub

composable-primitives

melodic-software

Design composable agentic primitives for flexible workflows. Use when creating reusable workflow building blocks, designing SDLC primitives, or building agent operations that can be combined in different ways.

GitHub

agent-specialization

melodic-software

Guide creation of focused single-purpose agents following the One Agent One Prompt One Purpose principle. Use when designing new agents, refactoring general agents into specialists, or optimizing agent context...

GitHub

ai-governance

melodic-software

AI governance and responsible AI planning including EU AI Act classification, NIST AI RMF, and AI ethics frameworks

GitHub

interview-conducting

melodic-software

AI-led stakeholder interviews using LLMREI research-backed patterns. Conducts structured interviews to elicit requirements through context-adaptive questioning, active listening, and systematic requirement extr...

GitHub

event-storming

melodic-software

AI-simulated event storming workshop with multi-persona support. Use when discovering domain events, commands, actors, and bounded contexts. Supports three modes - full-simulation (5 persona agents debate), qui...

GitHub

self-improve-prompt-design

melodic-software

Write self-improve prompts that sync expertise files with codebase reality. Use when creating maintenance workflows for agent experts, designing validation logic, or implementing the LEARN step of Act-Learn-Reu...

GitHub

orchestration-prompts

melodic-software

Write prompts for orchestrator workflows with phases and aggregation. Use when designing multi-phase workflows, writing agent command prompts, or implementing result aggregation patterns.

GitHub

agent-expert-creation

melodic-software

Create specialized agent experts with pre-loaded domain knowledge using the Act-Learn-Reuse pattern. Use when building domain-specific agents that maintain mental models via expertise files and self-improve pro...

GitHub

custom-agent-design

melodic-software

Design custom agents from scratch using Claude Agent SDK patterns. Use when building domain-specific agents, designing agents with full SDK control, or creating specialized agents with custom tools and prompts.

GitHub

ethics-review

melodic-software

AI and technology ethics review including ethical impact assessment, stakeholder analysis, and responsible innovation frameworks

GitHub

gemini-command-development

melodic-software

Expert guide for creating custom Gemini CLI commands. Covers slash command definitions (.toml), argument parsing, and shell execution. Use when creating custom Gemini commands, defining TOML command files, addi...

GitHub

claude-desktop

melodic-software

Central authority for Claude Desktop application - the native desktop app for running Claude Code sessions. Covers installation (macOS/Windows), Git worktrees for parallel sessions, .worktreeinclude file config...

GitHub

prompt-section-design

melodic-software

Design composable prompt sections for building agentic prompts. Use when creating reusable prompt components, designing LEGO-block prompt sections, or structuring prompts for the stakeholder trifecta.

GitHub

agent-lifecycle-management

melodic-software

Manage agent fleet through CRUD operations and lifecycle patterns. Use when creating, commanding, monitoring, or deleting agents in multi-agent systems, or implementing proper resource cleanup.

GitHub

orchestrator-design

melodic-software

Design O-Agent systems for multi-agent fleet management. Use when building orchestrator agents, designing multi-agent architectures, or creating unified interfaces for agent fleet control.

GitHub

gemini-cli-execution

melodic-software

Expert guide for executing the Google Gemini CLI in non-interactive and headless modes. Covers command syntax, piping input, output handling, and automation patterns. Use when running gemini commands, piping co...

GitHub

output-customization

melodic-software

Central authority for Claude Code output styles. Covers built-in output styles (Default, Explanatory, Learning), custom output styles, output style frontmatter (name, description, keep-coding-instructions), /ou...

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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