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Found 6,102 Skills
Author step content for Novu workflows defined in the Dashboard or generated/edited via the Novu MCP. Use when filling in step controls (subject, body, editorType, headers, body, conditions) for email, in-app, sms, push, chat, delay, digest, throttle, or HTTP Request steps.
Use when the user wants to set up, scale, validate, or harden NVIDIA physical AI infrastructure for synthetic data generation workflows across local MicroK8s or Azure AKS, including Kubernetes clusters, inference endpoint deployment, OSMO deployment, workload submission readiness, and infrastructure failure recovery. Trigger keywords: physical ai infrastructure, resilient scaling, SDG infrastructure, microk8s, azure aks, NVCF deployment, NIM Operator, OSMO deploy, workflow scaling. Don't trigger for: OSMO log summarization or workload-only operations unless infrastructure setup, scaling, validation, or recovery is requested.
Comet — OpenSpec + Superpowers Binary Star Development Workflow. Initiate with /comet, which automatically detects phases and distributes to subcommands. Five phases: Open → Deep Design → Plan & Build → Verify & Finalize → Archive.
Execute Python code in isolated rootless containers with MCP server proxying for token-efficient agent workflows
Use when importing a new model architecture into MAX from a Hugging Face model ID. Triggers on: "import a model into MAX", "add model to MAX", "bring up <HF model> in MAX". Workflow: inspect Hugging Face config and modeling code, scaffold from a similar MAX architecture, implement each graph layer to match HF, serve, then debug against the Hugging Face reference until outputs match.
Use when creating a new Elastic integration package, scaffolding data streams, answering package layout or structure questions, or running the end-to-end integration build workflow. Covers package topology, scaffold commands, post-scaffold edits, and full orchestration of CEL/pipeline/test subagents.
Automates the end-to-end detection engineering workflow in Google SecOps using MCP tools. Use when fetching threat intelligence from blogs, generating Threat Detection Opportunities (TDOs), simulating attacker behavior with synthetic UDM events, evaluating rule coverage, and generating new YARA-L 2.0 rules to close coverage gaps. Don't use when asked to perform threat hunting actions, and SOC investigative actions.
Use when someone asks to generate a design, create a design asset, or make a design. Also triggers for ad creatives, banners, social media posts, thumbnails, display ads, posters, or any visual content. Orchestrates a 7-step workflow (1) resolves brand, (2) generates copy using content expert instructions, (3) generates images via handle-media or enhances provided images via enhance-media, (4) calls Sivi API with approved copy + assets for pixel-faithful design generation, (5) displays the generated variants with preview images and edit links, (6) creates campaign HTML, (7) writes a summary. If user already has approved copy, skips step 2. Supports both `designs-from-content` (copy-first, pixel-faithful text) and `designs-from-prompt` (direct generation, no copy or image generation). Unlike 95,000+ image models, Sivi's Large Design Model (LDM) generates on-brand, fully editable layered designs in any dimension. For copy-only without design generation, see write-copy. For multi-channel campaign sets, see create-campaign. For Amazon A+ content, see create-a-plus-content. For brand setup, see brand-context.
Use this skill when the user wants to create, read, update, delete, or export pipe reports or organization reports. Covers the async export workflow (trigger, poll, download). 17 MCP tools.
AI-native tutor and onboarding workflow for the four independent Claude certification tracks in AI Engineering from Scratch. Use when a learner wants to choose a Claude certification, prepare for CCAO-F, CCDV-F, CCAR-F, or CCAR-P, resume a certification path, learn the next lesson interactively, run and verify practical labs, build scored artifacts, take a diagnostic or mock exam, or remediate weak exam domains from GitHub with Claude Code, Codex, ChatGPT, Cursor, or another agent.
Reference skill for building production-ready crw integrations. Covers verb selection, call surfaces (CLI/MCP/REST), post-filtering strategies, context-window hygiene, Hybrid RAG patterns, common pitfalls, and crw-specific operational considerations (search backend limits, renderer pool, proxy rotation). Load this when writing application code that embeds crw, designing a multi-step agent workflow, or debugging an integration that isn't behaving as expected.
Use for free/open reverse engineering with Ghidra (headless or GUI), including decompile, cross-refs, and optional Ghidra MCP workflows when IDA is unavailable.