Browse reusable instructions for your AI tools. Copy and customize a prompt, or download a skill for a supported agent.
Implement GDPR data protection requirements. Configure consent management, data subject rights, and privacy by design. Use when processing EU personal data.
Implement Git branching strategies, PR workflows, and release management patterns.
Build, test, and deploy applications using GitHub Actions workflows.
Configure GitLab CI/CD pipelines and runners for automated building, testing, and deployment.
Operate GPU-backed Kubernetes clusters for AI inference and training with scheduling, autoscaling, node health, MIG partitioning, and cost controls.
Set up and manage NVIDIA GPU servers for AI workloads
Manage secrets and PKI with HashiCorp Vault.
Create, manage, and deploy Helm charts for Kubernetes package management.
Implement HIPAA security and privacy rules. Configure PHI protections and BAA requirements. Use when handling healthcare data.
Set up and manage SSO, SCIM provisioning, and MFA for startup teams using Google Workspace, Okta, or Azure AD.
Implement incident management processes and escalation procedures. Configure on-call schedules and post-incident reviews. Use when managing production incidents.
Handle security incidents with IR playbooks and procedures.
Implement ISO 27001 Information Security Management System. Configure ISMS controls and risk management. Use when implementing enterprise security frameworks.
Create and manage Jenkins CI/CD pipelines, configure agents, manage plugins, and automate builds.
Implement Kubernetes security contexts, Pod Security Standards, and network policies.
Deploy, scale, and manage Kubernetes workloads.
Customize Kubernetes manifests without templating using Kustomize.
System administration for Linux servers. Manage packages, services, and system configuration. Use when administering Linux systems.
Apply CIS benchmarks and secure Linux servers.
Secure LLM-powered applications with input validation, output controls, tenant isolation, and abuse prevention.
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.
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.
Try another platform, a broader search, or fewer filters.
Explore all resourcesResource formats: Prompts are ready to copy into a conversation. Skills install into the compatible agent shown on their page.
How it worksInclude the instructions, intended platforms, author, and license. Submissions are reviewed before publication.