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Found 1,268 Skills
Authors and edits AWS Step Functions state machines: writes Amazon States Language (ASL) in JSONata, and chooses and structures state types (Task, Choice, Map, Parallel, Pass, Wait, Succeed, Fail). Covers ASL syntax, JSONata data transformation and variables, Retry/Catch error handling, service integrations (.sync, waitForTaskToken callbacks), Distributed Map for large-scale S3/CSV processing, saga/compensation patterns, Standard vs Express workflow choice, TestState API unit testing, and migrating state machines from JSONPath to JSONata. Use when the user is building, authoring, debugging, or migrating a Step Functions state machine or ASL definition, or orchestrating multi-step workflows with branching, retries, or human-approval callbacks, even if they don't say 'Step Functions.' Do NOT use for general Lambda function code, API Gateway, EventBridge wiring, or SAM/CDK application packaging.
Product marketing, positioning, GTM strategy, and competitive intelligence. Includes ICP definition, April Dunford positioning methodology, launch playbooks, competitive battlecards, and international market entry guides. Use when developing positioning, planning product launches, creating messaging, analyzing competitors, entering new markets, enabling sales, or when user mentions product marketing, positioning, GTM, go-to-market, competitive analysis, market entry, or sales enablement.
Help users create compelling product visions. Use when someone is writing a vision statement, defining a long-term product direction, aligning teams on the future state, or distinguishing vision from strategy.
Help users set effective OKRs and goals. Use when someone is creating quarterly objectives, defining key results, setting team goals, planning annual targets, or struggling with goal alignment across their organization.
Help users define their North Star metric. Use when someone is choosing their primary success metric, trying to align the team around a key measure, struggling with metric proliferation, or setting up their measurement strategy.
Create and manage datasets on Hugging Face Hub. Supports initializing repos, defining configs/system prompts, streaming row updates, and SQL-based dataset querying/transformation. Designed to work alongside HF MCP server for comprehensive dataset workflows.
Use this skill when users need to develop brand strategy, choose a company name, define brand positioning, create brand voice, or build brand identity from day one. Activates for "what should I name it," "brand strategy," "positioning," or identity questions.
TypeScript strict mode patterns, naming conventions, and type safety rules. Use when writing TypeScript code, defining types, or reviewing TypeScript projects. Includes generics, utility types, and best practices.
Provides Tambo with data and capabilities via custom tools, MCP servers, context helpers, and resources. Use when registering tools Tambo can call, connecting MCP servers, adding context to messages, implementing @mentions, or providing additional data sources with defineTool, mcpServers, contextHelpers, or useTamboContextAttachment.
Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts. BOOTSTRAP MODE - Triggers: "Create a data context skill", "Set up data analysis for our warehouse", "Help me create a skill for our database", "Generate a data skill for [company]" → Discovers schemas, asks key questions, generates initial skill with reference files ITERATION MODE - Triggers: "Add context about [domain]", "The skill needs more info about [topic]", "Update the data skill with [metrics/tables/terminology]", "Improve the [domain] reference" → Loads existing skill, asks targeted questions, appends/updates reference files Use when data analysts want Claude to understand their company's specific data warehouse, terminology, metrics definitions, and common query patterns.
Deploy prompt-based Azure AI agents from YAML definitions to Azure AI Foundry projects. Use when users want to (1) create and deploy Azure AI agents, (2) set up Azure AI infrastructure, (3) deploy AI models to Azure, or (4) test deployed agents interactively. Handles authentication, RBAC, quotas, and deployment complexities automatically.
Generates .NET Clean Architecture backend structure from entity definitions