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testing security llm ai AI 技能

发现 testing security 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: testing security llm ai

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GitHub

create-tia-agent

danja

Guides users through creating a new TIA XMPP agent based on mistral-minimal. Use when the user wants to create, build, set up, or scaffold a new agent, bot, or when they ask how to get started with TIA.

GitHub

claude-agent-sdk

jeongsk

Build production AI agents using the Claude Agent SDK (TypeScript/Python). Use this skill when the user asks about: (1) Building AI agents with Claude, (2) Using the @anthropic-ai/claude-agent-sdk or claude-age...

GitHub

langchain-framework

bobmatnyc

LangChain LLM application framework with chains, agents, RAG, and memory for building AI-powered applications. Use when implementing RAG (Retrieval Augmented Generation), creating AI agents with tools, or chain...

GitHub

dspy-framework

bobmatnyc

DSPy declarative framework for automatic prompt optimization treating prompts as code with systematic evaluation and compilers. Use when optimizing prompts systematically, building production LLM systems, imple...

GitHub

mcp

bobmatnyc

MCP (Model Context Protocol) - Build AI-native servers with tools, resources, and prompts. TypeScript/Python SDKs for Claude Desktop integration.

GitHub

draft-initialization

keberle

Initialize fiction draft cycles following the Spec-Kit workflow (idea → clarify → plan → tasks). Use when creating new drafts, planning rewrites, breaking down episodes, or structuring story changes. Triggers i...

GitHub

paper-writing

vishalsachdev

Expert guidance for writing high-quality academic and research papers. Use when the user wants to write, structure, revise, or improve academic papers, research articles, conference papers, or technical reports...

GitHub

llm-caching-patterns

yonatangross

Multi-level caching strategies for LLM applications - semantic caching (Redis), prompt caching (Claude/OpenAI native), cache hierarchies, cost optimization, and Langfuse cost tracking with hierarchical trace ro...

GitHub

streaming-api-patterns

yonatangross

Implement real-time data streaming with Server-Sent Events (SSE), WebSockets, and ReadableStream APIs. Master backpressure handling, reconnection strategies, and LLM streaming for 2025+ real-time applications.

GitHub

ai-native-development

yonatangross

Build AI-first applications with RAG pipelines, embeddings, vector databases, agentic workflows, and LLM integration. Master prompt engineering, function calling, streaming responses, and cost optimization for...

GitHub

design-system-starter

yonatangross

Use this skill when creating or evolving design systems for applications. Provides design token structures, component architecture patterns, documentation templates, and accessibility guidelines. Ensures consis...

GitHub

langgraph-workflows

yonatangross

Design and implement multi-agent workflows with LangGraph 0.2+ - state management, supervisor-worker patterns, conditional routing, and fault-tolerant checkpointing

GitHub

agent-awareness

eveld

ALWAYS check this skill before using grep, glob, Task tool, or doing any codebase exploration. Guides you to use specialized agents that are more efficient than basic tools.

GitHub

collaborative-outline

bahayonghang

This skill should be used when the user asks to "创建大纲", "outline", "文章结构规划", "plan article structure", or needs help structuring their content before writing. Provides collaborative outline creation w...

GitHub

prompt-writing

bcasci

Generates, analyzes, and optimizes prompts for skills, commands, subagents, reference docs, and free-form text. Use when generating prompt content, analyzing prompt files, or optimizing prompt text to apply tec...

GitHub

meta-prompt-framework

seanchatmangpt

Three-phase task execution framework with refinement strategies and role-specific prompting. Automatically activates when designing prompts, optimizing task flows, or implementing iterative improvement patterns...

GitHub

learning-design-checklist

vishalsachdev

Generate a quick compliance checklist from the Four Learning Design Pillars. Use when users want a practical checklist for reviewing content, a quick audit tool, or verification questions for specific pillars.

GitHub

candidate-kb

ewurch

Manage candidate knowledge base. Use when ingesting CVs, adding profile information, or querying candidate details for resume/cover letter generation.

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