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2,630 results in Infrastructure, Skills, Sub-Agents, Workflows · page 56 of 110
legal-advisor-2
Use this agent when you need to draft contracts, review compliance requirements, develop IP protection strategies, or assess legal risks for technology businesses. Specifically:\\n\\n<example>\\nContext: Startup is launching a SaaS product and needs to establish foundational legal protection before customer agreements.\\nuser: \"We need a Terms of Service, Privacy Policy, and GDPR compliance roadmap for our new SaaS product launching in 3 months. We're handling user data and need to ensure we're legally protected.\"\\nassistant: \"I'll develop a comprehensive legal framework: draft compliant ToS with liability limitations, create a Privacy Policy addressing GDPR and CCPA requirements, establish data processing procedures, design consent flows, and provide a compliance checklist with implementation timeline. I'll also identify key jurisdictions to address and potential gaps in your current data handling.\"\\n<commentary>\\nUse legal-advisor when launching products or services that require legal infrastructure like ToS, privacy policies, or data handling compliance. This covers multi-jurisdictional requirements and proactive legal framework setup.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: Company is signing significant vendor contracts and needs risk assessment before commitment.\\nuser: \"We're evaluating a major cloud infrastructure contract with AWS. Can you review this agreement and identify risky clauses, liability exposures, and negotiation points? We want to understand what we're signing up for.\"\\nassistant: \"I'll conduct a detailed contract analysis: identify liability caps and indemnification issues, flag unclear SLA terms, assess penalty clauses, review data ownership and security requirements, highlight auto-renewal and termination provisions, and prioritize negotiation points by risk level. I'll provide specific recommended language changes and fallback positions.\"\\n<commentary>\\nInvoke legal-advisor when reviewing or negotiating vendor contracts, partnership agreements, or other binding commitments. This focuses on protecting business interests while identifying negotiable terms.\\n</commentary>\\n</example>\\n\\n<example>\\nContext: Tech company wants to strengthen IP protection and avoid infringement risks.\\nuser: \"We need to audit our intellectual property strategy. We've built proprietary algorithms and tools, and we want to understand: should we patent, what trade secrets need protecting, do we need trademark registration? Also checking if we're infringing anything.\"\\nassistant: \"I'll develop a comprehensive IP strategy: assess patentability of your algorithms, recommend trademark registration approach for your brand and tools, establish trade secret protection procedures, create employee IP assignment policies, conduct competitive analysis to identify infringement risks, and propose licensing agreements for any third-party dependencies.\"\\n<commentary>\\nUse legal-advisor for intellectual property strategy when you need to protect proprietary technology, establish trademark/patent strategy, or assess infringement risks. This is critical before product launch or significant funding rounds.\\n</commentary>\\n</example>
lightpanda
Ultra-fast headless browser written in Zig specifically for AI and automation workloads. It runs JavaScript natively, uses 9x less memory than Chrome headless, and targets sub-100ms page execution.
linkedin-profile-optimizer
Optimize a LinkedIn profile for searchability, recruiter visibility, and engagement. Use when the user mentions LinkedIn profile, headline, About section, recruiter visibility, or social hiring.
lint-and-validate
Automatic quality control, linting, and static analysis procedures. Use after every code modification to ensure syntax correctness and project standards. Triggers onKeywords: lint, format, check, validate, types, static analysis.
linux-privilege-escalation
This skill should be used when the user asks to "escalate privileges on Linux", "find privesc vectors on Linux systems", "exploit sudo misconfigurations", "abuse SUID binaries", "exploit cron jobs for root access", "enumerate Linux systems for privilege escalation", or "gain root access from low-privilege shell". It provides comprehensive techniques for identifying and exploiting privilege escalation paths on Linux systems.
linux-production-shell-scripts
This skill should be used when the user asks to "create bash scripts", "automate Linux tasks", "monitor system resources", "backup files", "manage users", or "write production shell scripts". It provides ready-to-use shell script templates for system administration.
llama-cpp
Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.
llamaguard
Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.
llamaindex
Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.
llava
Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.
llm-app-patterns
Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.