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Found 1,333 Skills
Workflow for learning CuTe Python DSL by reading, importing, profiling, and extracting reusable patterns from CUTLASS Blackwell example kernels. Use when: (1) studying CUTLASS CuTe DSL reference implementations, (2) importing CUTLASS examples into the project runtime infrastructure, (3) building CuTe DSL knowledge base entries from profiling experiments, (4) understanding CuTe DSL API patterns, TMA pipelining, warpgroup scheduling, or persistent kernel structure.
Choose before `admin` when the user needs **Shopify CLI** to run or fix something now: validate app or extension config on disk (`shopify.app.toml`, `shopify.app.<name>.toml`, `shopify.extension.toml`) with **`shopify app config validate --json`** (not Admin GraphQL; MCP has no TOML validator); run or troubleshoot store workflows (`shopify store auth`, `shopify store execute`); inventory or product changes by handle, SKU, or location name; or CLI setup, auth, upgrade issues. Emphasize **commands and operational steps**, not only authoring GraphQL. Skip for API-only understanding or codegen with no CLI execution. Examples: validate before deploy; run an existing query via CLI; list products; missing `shopify store execute`.
Verint Open Platform help — enterprise CX automation with Da Vinci AI bots (Quality Bot 100% QA, Coaching Bot real-time guidance, Wrap Up Bot auto-summaries, CX/EX Scoring, TimeFlex agent scheduling, Exact Transcription 80+ languages), WFM forecasting/scheduling/adherence, knowledge automation, IVA virtual assistants, speech/text analytics, financial compliance, Verint Marketplace 350+ listings. Use when Verint reports loading slowly or showing inconsistent data, Quality Bot not scoring interactions correctly, Coaching Bot recommendations irrelevant, WFM forecasts off vs actual volume, Verint API integration or developer portal questions, comparing Verint vs NICE vs Genesys WEM capabilities, or connecting Verint to your CCaaS or CRM. Do NOT use for choosing between CCaaS platforms (use /sales-ccaas-selection) or for QA tool comparison across vendors (use /sales-coaching).
Use this skill when the user asks to call an authenticated HTTP API (for example "call the GitHub/OpenAI/Slack API", "hit an endpoint that needs a bearer token") and the `sesame` CLI is already installed on this device. The agent invokes `sesame request`, which forwards the HTTP call through the user's own broker and attaches the auth header server-side. The skill does not install software, does not read credentials from the environment, and runs shell only within the fixed `sesame` subcommand surface (`request`, `status`, `hostnames`, `login`, `refresh`). Skip for unauthenticated public endpoints, localhost services, or when the user has already exported a token in the environment for direct use.
Check and resize images for social media platforms. Run scripts/check.js to validate any image against specs for Instagram, Facebook, X (Twitter), LinkedIn, TikTok, YouTube, Pinterest, Snapchat, and Threads — get a ranked match list with exact resize commands. Run scripts/resize.js to export a correctly-sized copy. Use when a user asks to validate image dimensions, resize an image for a platform, check if an image fits a spec, or prep assets for social media posting or ads.
Learn how to implement the Syncfusion Angular Carousel component for displaying slides with images and content. This comprehensive skill includes complete API documentation with all 30 properties, 5 methods, 2 events, and working code examples. Use when creating image galleries, product showcases, featured content sliders, news rotators, or implementing carousel navigation with animations.
Adversarial robustness engineering for ML/AI—evasion, poisoning, extraction, membership-inference threat models; robust training, sanitization, detectors; ASR/certified evals; lab model attacks; data-pipeline integrity; production I/O guardrails (classical ML and LLM/multimodal). Use for adversarial examples, robustness suites, poison audits, deploy guardrails—not LLM app red team (ai-redteam), governance (ai-risk-governance), safety classifier R&D (ml-research-engineer-safeguards), safeguard serving (ml-infrastructure-engineer-safeguards), privacy research (privacy-research-engineer-safeguards), AppSec pentest (penetration-tester).
Run Megatron-LM (MLM) and Megatron Bridge training with mock or real data. Covers correlation testing, available recipes, and multi-GPU examples.
Define brand voice using NN/g four dimensions, Aaker brand personality, and Jung archetypes. Produces scored voice dimensions, vocabulary lists, and on-brand vs off-brand examples. Triggers when someone needs voice guidelines, tone of voice, "how should we sound", or writing style guidance.
Official NVIDIA-authored guidance for navigating PhysicsNeMo — pick the model, datapipe, or example for a SciML/AI4Science task (surrogates, forecasting, downscaling, physics-informed, inverse, generative). Points at existing files via live repo search; never writes code. Do NOT use for installation or environment setup, training-loop or other code authoring/scaffolding, contributor/CI/packaging questions, repo-specific questions in physicsnemo-sym/-cfd/-curator, or general (non-physics) ML/PyTorch.
Parses Amazon Search Term Reports (50K+ rows) into 4 actionable buckets: negative exacts, negative phrases, exact-match harvest, and hero scale terms. Produces a Bulk Operations upload-ready file in minutes instead of the eyeball approach that misses 60% of opportunities. Use when a user mentions STR, PPC bulksheet, or search term analysis. Trigger phrases: "search term report", "STR analysis", "PPC bulksheet", "negative keywords bulk upload", "harvest exact match". Works with zero tools.
Amazon OpenSearch Service and Serverless across five capabilities — migration (Solr/ES/self-managed OpenSearch into AOS/AOSS, schema/query translation, sizing, cutover); provisioning (domain + AOSS lifecycle, upgrades, storage tiers, FGAC, monitoring); search (vector / semantic / hybrid / RAG with Bedrock connectors); log-analytics (PPL, OSI ingestion, anomaly detection, OpenSearch Dashboards, Splunk/Datadog alternatives); trace-analytics (OTel spans, service maps, Data Prepper). Triggers on OpenSearch, AOS, AOSS, Elasticsearch, ELK, Solr, Lucene, vector / k-NN / semantic / hybrid / neural search, RAG, ELSER, log analytics, observability, Kibana, OSI, OCU, PPL, trace analytics, BM25, eDisMax, schema.xml, ILM, ISM, FAISS, HNSW, Migration Assistant for Amazon OpenSearch Service, Historical Data Migration, Live Traffic Migration, UltraWarm, OR1, Splunk/Datadog alternative, moving off Solr. Picks ONE capability per ask, names instance class + count + shard math, ships query DSL examples.