GitHub
firecrawl
Web scraping, content extraction, and autonomous research agent for deep web investigation.
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devops llm ai AI 技能
发现 devops llm ai 相关 Skills，比较来源仓库和用途，查看适合你工作流的技能说明。
分类目录: devops llm ai
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GitHub
advanced-evaluation
LLM-as-Judge techniques including direct scoring, pairwise comparison, rubric generation, and bias mitigation.
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GitHub
healer
Healer monitoring expertise - detection patterns, API endpoints, dual-model architecture, and remediation workflows. Use when monitoring Play workflows or debugging agent failures.
☆ 1查看技能
GitHub
deep-research
Deep technical research using Firecrawl Agent for autonomous web investigation, competitive analysis, and implementation pattern discovery.
☆ 1查看技能
GitHub
openmemory
Persistent long-term agent memory for storing and querying past work, patterns, and learnings.
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GitHub
evaluation
Agent evaluation methods including LLM-as-judge, rubrics, and quality gates.
☆ 1查看技能
GitHub
ai-ml-infra
KubeAI, GPU operators, and model serving patterns for AI/ML infrastructure on Kubernetes.
☆ 1查看技能
GitHub
ralph-technique
The Ralph Wiggum technique for minimal, declarative prompts that enable loop-based autonomous execution.
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GitHub
skill-authoring
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...
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GitHub
bun-llm-docs
Fetch Bun runtime documentation via llms.txt for up-to-date API references
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GitHub
project-development
Methodology for identifying LLM-suited tasks, designing pipelines, and iterating with agent-assisted development.
☆ 1查看技能
GitHub
linear-agent-api
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.
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GitHub
llm-docs
Fetch LLM-optimized documentation from llms.txt endpoints for up-to-date API references
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GitHub
mcp-development
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...
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GitHub
context-degradation
Recognize and mitigate context failures including lost-in-middle, context poisoning, distraction, confusion, and clash.
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GitHub
context-fundamentals
Foundational understanding of context engineering for AI agent systems - context windows, attention mechanics, progressive disclosure, and context budgeting
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GitHub
tool-design
Design effective tools for AI agents - tool descriptions, consolidation principles, architectural reduction, MCP naming conventions, and error handling
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GitHub
frontend-design
Create distinctive, production-grade frontend interfaces with high design quality. Use when building UI components, pages, or applications to avoid generic AI aesthetics.
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GitHub
mcp-manager
Conversational interface for managing MCP (Model Context Protocol) server configurations in Claude Code
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GitHub
meme-generation
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...
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GitHub
persona-creation
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...
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GitHub
jules-api
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...
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GitHub
errors
Error Handling skill for the ikigai project
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GitHub
meta
Meta - Agent System infrastructure for the ikigai project
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默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。