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Found 6,275 Skills
Preview an existing saved CARTO Builder map inline in the chat via the CARTO MCP server's load_builder_map tool. Use whenever the user references a saved Builder map — by URL, by ID, or by name (resolved via list_maps first). Renders a lightweight read-only preview (layers, basemap, viewport, popups, legend). Widgets, SQL parameters, map description, and other Builder-only features are NOT included; the user can click "Open in Builder" for the full experience. Triggers on "show me the X map", "open the Y map", "preview the Z map", and post-CLI-creation inline previews of a freshly-created map. Distinct from carto-create-builder-maps (CLI authoring), carto-render-inline-map (ad-hoc deck.gl spec), and carto-develop-app (developer app).
Writes, reviews, and debugs idiomatic Rust code with memory safety and zero-cost abstractions. Implements ownership patterns, manages lifetimes, designs trait hierarchies, builds async applications with tokio, and structures error handling with Result/Option. Use when building Rust applications, solving ownership or borrowing issues, designing trait-based APIs, implementing async/await concurrency, creating FFI bindings, or optimizing for performance and memory safety. Invoke for Rust, Cargo, ownership, borrowing, lifetimes, async Rust, tokio, zero-cost abstractions, memory safety, systems programming.
Migrates Airflow projects from airflow-ai-sdk to apache-airflow-providers-common-ai 0.1.0+. Use this skill when the user wants to replace airflow-ai-sdk with the official Airflow AI provider, migrate LLM decorators (@task.llm, @task.agent, @task.llm_branch, @task.embed), switch from model strings/objects to connection-based LLM configuration, or update imports from airflow_ai_sdk to the new provider. Also trigger when the user mentions common-ai provider, AIP-99, pydanticai connection, or migrating away from airflow-ai-sdk.
Deploys and manages Laravel applications on Laravel Cloud using the `cloud` CLI. Use when the user wants to deploy an app, ship to cloud, create/manage environments, databases, caches, domains, instances, background processes, or any Laravel Cloud infrastructure. Triggers on deploy, ship, cloud management, environment setup, database provisioning, and similar cloud operations.
Designs and optimizes Clay-powered GTM workflows for prospecting, signal detection, outbound email sequences, enrichment pipelines, and account-based marketing. Use when the user mentions 'Clay,' 'GTM engineering,' 'prospecting,' 'signal detection,' 'enrichment,' 'Claygent,' 'outbound automation,' or wants to build Clay tables or integrate with sequencing tools like Lemlist, Smartlead, or Instantly.
Last-minute hotel deals with a local price-history database no HotelTonight client has — snapshot deals over time,... Trigger phrases: `find a last-minute hotel tonight`, `watch this city for hotel price drops`, `is this hotel price a good deal`, `what's the daily drop in San Francisco`, `cheapest hotel night this weekend`, `use hotel-tonight`, `run hotel-tonight`.
Use version control as a craft — atomic commits, buildable history, useful PRs, bisect-friendly main, recoverable mistakes. Use this skill whenever the task involves writing commits or PRs, choosing a branching model, deciding rebase vs. merge, recovering from a force-push or accidentally-committed secret, debugging a regression with `git bisect`, structuring a long change as a series of small reviewable steps, or judging whether a repo's history is readable. Use it especially when reviewing commit messages, PR descriptions, branching strategies, or merge policies. Built on Tim Pope and Chris Beams on commit messages, Paul Hammant on trunk-based development, Vincent Driessen on GitFlow (and his 2020 note retiring it for SaaS), Linus Torvalds on never rebasing public commits, and the Google Engineering Practices CL guide.
Use when operating the vigolium CLI for web vulnerability scanning, security testing, traffic ingestion, server management, AI agent-driven scanning and code review, cloud-storage management, or writing custom JavaScript extensions. Invoke for scan commands, scan-url, scan-request, run, ingest, server, agent (query/autopilot/swarm/olium/piolium/audit/session), traffic browsing, database queries, storage uploads/downloads, module management, extension scripting, export, project management, and configuration tuning.
Comprehensive markdown and Mermaid diagram writing skill. Use when creating any scientific document, report, analysis, or visualization. Establishes text-based diagrams as the default documentation standard with full style guides (markdown + mermaid), 24 diagram type references, and 9 document templates.
Audit your biggest closed-won deals to find your PROVEN ideal customer profile, then find more accounts like them. Use whenever someone wants to analyze won deals, audit their best customers, see which companies generated the most revenue, find their real ICP, build a look-alike target list, segment customers by what actually pays, or learn which acquisition channel produced their best revenue. Triggers on: 'audit my biggest deals', 'which customers made us the most money', 'analyze my closed-won', 'what's my proven ICP', 'find more customers like my best ones', 'look-alike accounts', 'HubSpot deal analysis', 'revenue by account', 'which channel generated my best deals', 'acquisition source analysis'. For RevOps, Heads of Sales/Marketing, founders and growth leads doing ICP refinement, account-based targeting or pipeline/QBR review. Reads HubSpot via its MCP or a CSV export, then hands the profile to sales-nav-search-builder to generate the prospecting search. Maintained by La Growth Machine.
Cram Engine - An AI tutor well-versed in learning science. Triggered when users mention terms like final exam cramming, final review, exam sprint, last-minute exam preparation, quick exam prep, intensive last-minute review, or use the /cram command. Based on six learning science principles including Cognitive Load Theory, Elaborative Processing, Generation Effect, and Retrieval Practice, it converts key points of university courses into efficient interactive learning sessions through a four-stage pipeline: deconstructing knowledge point tree → teaching each point individually → testing with real exam question types → diagnosing and filling knowledge gaps. Suitable for all qualitative knowledge-intensive university liberal arts courses.
DINO (DETR with Improved DeNoising Anchor Boxes) for 2D object detection. Transformer-based detector with denoising training, multi-scale features, and optional distillation support. Use when training, evaluating, exporting, distilling, quantizing, or running inference for a TAO DINO detector. Trigger phrases include "train DINO", "DETR object detection", "TAO 2D detection", "DINO with distillation".