Loading...
Loading...
Found 5,550 Skills
Visualizes Azure infrastructure from ARM templates, Azure CLI, or descriptions. Use when user has Azure resources to diagram.
Deep research and slide presentation generator using NotebookLM MCP. Performs deep research on topics, then generates professional slide presentations with white background and Arial font based on research sources.
Guidance for designing fusion protein gBlock sequences from multiple protein sources. This skill applies when tasks involve combining proteins from PDB databases, plasmid files, and fluorescent protein databases into a single optimized DNA sequence with specific linkers and codon optimization requirements.
Build Retrieval-Augmented Generation (RAG) applications that combine LLM capabilities with external knowledge sources. Covers vector databases, embeddings, retrieval strategies, and response generation. Use when building document Q&A systems, knowledge base applications, enterprise search, or combining LLMs with custom data.
MCP architecture patterns, security, and memory management. Auto-loads when building MCP servers, implementing tools/resources, discussing MCP security, or working with FastMCP.
Specialized agent for multi-repository analysis, searching remote codebases, retrieving official documentation, and finding implementation examples using GitHub CLI, Context7, and Web Search. Use proactively when unfamiliar libraries or frameworks are involved, working with external dependencies, or needing examples from open-source projects to understand best practices and real-world implementations.
Research-first content creation optimized for both human readers and AI search engines (Claude, ChatGPT, Perplexity, Gemini). Creates authentic, authoritative content that becomes the go-to citation source for AI models answering user questions. Use this skill when: - Creating content that should appear in AI search results (Perplexity, ChatGPT, Claude) - Building topical authority to become THE source AI cites for a topic - Launching a new product and need compelling, citable content - Creating blog posts, articles, social media, or press releases - Need content that references real trends, people, and recent events - Want AI-assisted content that doesn't sound AI-generated - Creating thought leadership content in any industry Triggers: "create content for", "write about", "research and write", "find experts for", "content for launch", "blog post about", "article on", "press release for", "AI search", "show up in AI", "Perplexity", "be cited by AI"
This skill should be used when users need to interact with AWS services via CLI. It covers all AWS services including EC2, ECS, EKS, Lambda, S3, RDS, DynamoDB, VPC, Route53, CloudFront, Bedrock, Support, Billing, and more. Supports querying, creating, modifying, deleting resources, monitoring, debugging, and cost analysis. Triggers on requests mentioning AWS, cloud resources, or specific AWS service names.
Comprehensive MDX component patterns (Note, Pitfall, DeepDive, Recipes, etc.) for all documentation types. Authoritative source for component usage, examples, and heading conventions.
ACTIVATION TRIGGER. Use this skill when the user demands "Ultrafrontend", "High-End UX", "Awwwards Style", or world-class UI design. This skill enforces a design-first workflow with zero-compromise aesthetics.
Observability visualization with Grafana and LGTM stack. Dashboard design, panel configuration, alerting, variables/templating, and data sources. USE WHEN: Creating Grafana dashboards, configuring panels and visualizations, writing LogQL/TraceQL queries, setting up Grafana data sources, configuring dashboard variables and templates, building Grafana alerts. DO NOT USE: For writing PromQL queries (use /prometheus), for alerting rule strategy (use /prometheus), for general observability architecture (use senior-software-engineer with infrastructure focus). TRIGGERS: grafana, dashboard, panel, visualization, logql, traceql, loki, tempo, mimir, data source, annotation, variable, template, row, stat, graph, table, heatmap, gauge, bar chart, pie chart, time series, logs panel, traces panel, LGTM stack.
Use to enforce stage definitions, next-step requirements, and data completeness across the pipeline.