LEX: Legal-Entity-X-ref
Structured research aid for cross-jurisdictional legal context (US, EU, CA) and contract scaffolding.
Browse reusable instructions for your AI tools. Copy and customize a prompt, or download a skill for a supported agent.

Structured research aid for cross-jurisdictional legal context (US, EU, CA) and contract scaffolding.
Review Bitcoin Lightning Network protocol designs, compare channel factory approaches, and analyze Layer 2 scaling tradeoffs. Covers trust models, on-chain footprint, consensus requirements, HTLC/PTLC compatibility, liveness, and watchtower support.
Technical reference on Lightning Network channel factories, multi-party channels, LSP architectures, and Bitcoin Layer 2 scaling without soft forks. Covers Decker-Wattenhofer, timeout trees, MuSig2 key aggregation, HTLC/PTLC forwarding, and watchtower breach detection.
Explain Bitcoin Lightning channel factories and the SuperScalar protocol — scalable Lightning onboarding using shared UTXOs, Decker-Wattenhofer trees, timeout-signature trees, MuSig2, and Taproot. No soft fork required.
Automate Linear tasks via Rube MCP (Composio): issues, projects, cycles, teams, labels. Always search tools first for current schemas.
High-intent expert for LinkedIn profile checks and SEO optimization. Silently audits and rewrites profiles, delivering only the finished, ready-to-paste result.
Production patterns for Linkerd service mesh - the lightweight, security-first service mesh for Kubernetes.
System administration for Linux servers. Manage packages, services, and system configuration. Use when administering Linux systems.
Apply CIS benchmarks and secure Linux servers.
Execute systematic privilege escalation assessments on Linux systems to identify and exploit misconfigurations, vulnerable services, and security weaknesses that allow elevation from low-privilege user access to root-level control.
Provide production-ready shell script templates for common Linux system administration tasks including backups, monitoring, user management, log analysis, and automation. These scripts serve as building blocks for security operations and penetration testing environments.
Secure LLM-powered applications with input validation, output controls, tenant isolation, and abuse prevention.
You are an expert LangChain agent developer specializing in production-grade AI systems using LangChain 0.1+ and LangGraph.
Improve LLM prompts using task-specific evaluation, structured instructions, and regression checks.
Implement multi-layer LLM caching with exact match, semantic similarity, and provider-side prompt caching.
Reduce LLM API and infrastructure costs through model selection, prompt caching, batching, caching, quantization, and self-hosting strategies.
Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing.
Set up infrastructure for fine-tuning LLMs with QLoRA, LoRA, and full fine-tuning using Hugging Face TRL, Axolotl, and distributed training with DeepSpeed or FSDP.
Deploy an API gateway for LLM traffic with load balancing, rate limiting, key management, semantic caching, fallback routing, and cost tracking.
Auto-scale LLM inference clusters on Kubernetes using KEDA, custom GPU metrics, and horizontal pod autoscaling.
LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.
Use when improving prompts for any LLM. Applies proven prompt engineering techniques to boost output quality, reduce hallucinations, and cut token usage.
Authorized security assessment of LLM applications and AI agents: prompt injection, tool abuse, RAG exposure, memory poisoning, system-prompt extraction, and agent-compliance engineering per OWASP LLM/ASI Top 10.
Get reliable JSON, enums, and typed objects from LLMs using response_format, tool_use, and schema-constrained decoding across OpenAI, Anthropic, and Google APIs.
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How it worksInclude the instructions, intended platforms, author, and license. Submissions are reviewed before publication.