firecrawl
Web scraping, content extraction, and autonomous research agent for deep web investigation.
Découvrez les skills devops llm ai, comparez leurs dépôts et consultez leurs instructions.
Web scraping, content extraction, and autonomous research agent for deep web investigation.
LLM-as-Judge techniques including direct scoring, pairwise comparison, rubric generation, and bias mitigation.
Healer monitoring expertise - detection patterns, API endpoints, dual-model architecture, and remediation workflows. Use when monitoring Play workflows or debugging agent failures.
Deep technical research using Firecrawl Agent for autonomous web investigation, competitive analysis, and implementation pattern discovery.
Persistent long-term agent memory for storing and querying past work, patterns, and learnings.
Agent evaluation methods including LLM-as-judge, rubrics, and quality gates.
KubeAI, GPU operators, and model serving patterns for AI/ML infrastructure on Kubernetes.
The Ralph Wiggum technique for minimal, declarative prompts that enable loop-based autonomous execution.
Meta-skill for creating and improving agent skills. Use when designing new skills, refining existing skills, or understanding skill architecture patterns. Provides progressive disclosure, context efficiency pri...
Fetch Bun runtime documentation via llms.txt for up-to-date API references
Methodology for identifying LLM-suited tasks, designing pipelines, and iterating with agent-assisted development.
Linear Agent API expertise - sessions, activities, signals, and best practices. Use when working with Linear agent integration, verifying dialogue population, or implementing two-way communication.
Fetch LLM-optimized documentation from llms.txt endpoints for up-to-date API references
Guide for creating MCP (Model Context Protocol) servers that enable LLMs to interact with external services. Use when building MCP servers, integrating external APIs, implementing tool servers, or creating agen...
Recognize and mitigate context failures including lost-in-middle, context poisoning, distraction, confusion, and clash.
Foundational understanding of context engineering for AI agent systems - context windows, attention mechanics, progressive disclosure, and context budgeting
Design effective tools for AI agents - tool descriptions, consolidation principles, architectural reduction, MCP naming conventions, and error handling
Create distinctive, production-grade frontend interfaces with high design quality. Use when building UI components, pages, or applications to avoid generic AI aesthetics.
Conversational interface for managing MCP (Model Context Protocol) server configurations in Claude Code
Generate relevant memes using the memegen.link API. Use this skill when users request memes, want to add humor to content, or need visual aids for social media. Supports hundreds of popular meme templates with...
Master the art of creating effective AI agent personas for Jules. Learn how to design role-specific prompts that guide Jules to execute tasks with precision, following best practices, and maintaining project st...
Delegate asynchronous coding tasks to Jules (Google's AI coding agent) to maximize efficiency. Use for code reviews, refactoring, adding tests, bug fixes, and documentation. Proactively suggest Jules delegation...
Error Handling skill for the ikigai project
Meta - Agent System infrastructure for the ikigai project
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.