openai-image-gen
Batch-generate images via OpenAI Images API. Random prompt sampler + `index.html` gallery.
发现 tools 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。
Batch-generate images via OpenAI Images API. Random prompt sampler + `index.html` gallery.
Delegates coding tasks to Coco CLI (Codebase Copilot) for prototyping, debugging, and code review. Use when needing algorithm implementation, bug analysis, or code quality feedback. Supports multi-turn sessions...
Search and retrieve official Microsoft documentation, code samples, and technical information. Use PROACTIVELY when researching Azure AI Search, Copilot Studio, Azure Cognitive Services, Azure App Service, Micr...
Use this skill when the user asks to save, remember, recall, or organize memories. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check your notes', 'clean up memories'...
Generate comprehensive specification documents including requirements, technical design, and detailed task breakdown from any feature request. Use when the user asks to create specs, requirements docs, design d...
Comprehensive guide for building Agent Skills according to agentskills.io specification. Use when developers need to create, structure, or validate skills that follow the Agent Skills standard format and best p...
Analyzes Rust code for performance bottlenecks, memory inefficiencies, and optimization opportunities. Use when discussing performance, slow code, memory usage, profiling, benchmarks, or optimization.
Industrial-strength NLP with spaCy 3.x for text processing and custom classifier training. Use when "installing spaCy", "selecting model for nlp" (en_core_web_sm/md/lg/trf), "tokenization", "POS tagging", "name...
Synthesize consensus implementation plan from multi-agent debate reports using external AI review
Guide for distinguishing Claude Code features (Commands, Skills, Agents, Hooks, Rules) and selection criteria. Use when decomposing context files, deciding where to add new features, or customizing Claude Code.
Master model serving - inference optimization, scaling, deployment, edge serving
Expert guidance on 9 programming languages and 10+ frameworks. Compare, select, and master language ecosystems.
Systematic vulnerability finding, threat modeling, and attack surface analysis for AI/LLM security assessments
Implement mitigations, create input filters, design output guards, and build defensive prompting for LLM security
Tools and frameworks for AI red teaming including PyRIT, garak, Counterfit, and custom attack automation
Generate adversarial inputs, edge cases, and boundary test payloads for stress-testing LLM robustness
Techniques to test and bypass AI safety filters, content moderation systems, and guardrails for security assessment
Attack techniques for Retrieval-Augmented Generation systems including knowledge base poisoning
Securing AI/ML infrastructure including model storage, API endpoints, and compute resources
Implementing safety filters, content moderation, and guardrails for AI system inputs and outputs
Security best practices for deploying AI/ML models to production environments
Advanced prompt manipulation including direct attacks, indirect injection, and multi-turn exploitation
Advanced LLM jailbreaking techniques, safety mechanism bypass strategies, and constraint circumvention methods
Test AI systems for code injection vulnerabilities including prompt-to-code attacks and agent exploitation
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。