Skills
18,283 skills, most installed first.
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tao-run-automl-deft-pipelinenvidia1.6KRun the canonical NVIDIA AOI three-phase training pipeline — Phase 1 AutoML baseline (HPO), Phase 2 DEFT loop (RCA → SDG → mining → plain-train retrain), Phase 3 AutoML refinement on the DEFT-augmented dataset. Use when the user asks to "run the AOI workflow", "fine-tune my PCB AOI model end-to-end", "improve my AOI ChangeNet model", or "AOI workflow with AutoML" request — route here instead of tao-run-deft-aoi directly unless the user explicitly asks for the DEFT loop ONLY (e.g. "run JUST the Dtao-train-centerposenvidia1.6KCenterPose for keypoint / pose estimation. Detects object centers and regresses keypoint locations for 6-DoF object pose estimation. Use when training, evaluating, exporting, or running inference for a TAO CenterPose model. Trigger phrases include "train CenterPose", "6-DoF object pose", "keypoint estimation", "object pose regression".tao-train-segformernvidia1.6KSegFormer for semantic segmentation. Lightweight transformer-based architecture with hierarchical feature extraction, efficient for real-time segmentation tasks. Use when training, evaluating, exporting, quantizing, or running inference for a TAO SegFormer model. Trigger phrases include "train SegFormer", "semantic segmentation", "lightweight transformer segmenter", "real-time semantic segmentation".convex-security-auditwaynesutton1.6KDeep security review of a Convex app: authorization model, data access paths per table, HTTP action exposure, rate limiting, file storage access, scheduled function trust, and a written findings report. Use before launch, after an incident, or when the user asks for a full audit rather than a quick check.speckit-implementdceoy1.6KExecute the implementation plan by processing and executing all tasks defined in tasks.mdmapbox-search-patternsmapbox1.6KExpert guidance on choosing the right Mapbox search tool and parameters for geocoding, POI search, and location discoverytao-run-deft-aoinvidia1.6KRun the full DEFT AOI improvement loop for NVIDIA TAO VisualChangeNet / ChangeNet PCB inspection models: baseline evaluate, RCA, Cosmos AnomalyGen / AMP synthetic defects, k-NN mining, retraining, and deployment gating against a customer-defined primary metric and optional constraints. Use only when the request identifies an AOI / automated-optical-inspection, PCB-defect, VisualChangeNet, or ChangeNet workflow. Supports air-gapped/offline runs with pre-staged assets. Never infer AOI from generictao-train-mask-auto-encodernvidia1.6KMasked Auto-Encoder (MAE) for self-supervised pretraining and fine-tuning. Masks random patches and reconstructs them to learn visual representations; supports pretrain and finetune stages. Use when training, evaluating, exporting, or running inference for a TAO MAE backbone. Trigger phrases include "pretrain MAE", "self-supervised vision pretraining", "Masked Autoencoder", "Mask Auto-Encoder", "MAE fine-tune".crypto-ta-analyzerdkyazzentwatwa1.6KRun multi-indicator technical analysis on crypto or market OHLCV data. Use for deterministic trend, momentum, volume, and divergence analysis.huggingface-besthuggingface1.6KUse when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers on: "best model for X", "what model should I use for", "top models for [task]", "which model runs on my laptop/machine/device", "recommend a model for", "what LLM should I use for", "compare models for", "what's state of the art for", or any question about choosing an AI model for a specific use case. Always use this skihuggingface-local-modelshuggingface1.6KUse to select models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm. Covers finding GGUFs, quant selection, running servers, exact GGUF file lookup, conversion, and OpenAI-compatible local serving.tao-run-on-brevnvidia1.6KRun a TAO training/evaluation/inference container on an NVIDIA Brev GPU instance. Instance provisioning (create/search/stop/delete/login) is delegated to the official brev-cli agent skill or the Brev MCP server; this skill covers only the TAO-specific part — running the container over `brev exec` via the four-verb docker contract. Trigger phrases include "run on Brev", "Brev GPU instance", "TAO on Brev", "submit job to Brev".tao-train-mask-auto-labelnvidia1.6KMAL (Mask Auto-Label) for weakly-supervised segmentation. Produces segmentation masks from minimal annotations (point or box annotations) using a ViT-MAE backbone. Use when training, evaluating, or running inference for a TAO MAL model. Trigger phrases include "train MAL", "Mask Auto-Label", "weakly-supervised segmentation", "box-prompted segmentation", "minimal-annotation mask prediction".tao-train-pointpillarsnvidia1.6KPointPillars for 3D object detection from LiDAR point clouds. Encodes point clouds into a pseudo-image via a pillar-based representation, then applies 2D detection — used in autonomous driving and robotics. Use when training, evaluating, exporting, pruning, retraining, or running inference for a TAO PointPillars model. Trigger phrases include "train PointPillars", "LiDAR 3D detection", "point-cloud object detection", "pillar-based 3D detector".tao-train-single-stepnvidia1.6KStandard single-step train/eval/export workflow for any TAO model. Use when training a TAO model on a dataset without iterative data augmentation, AutoML, or DEFT loops. Trigger phrases include "single train run", "train then evaluate then export", "plain TAO training", "normal training", "no AutoML", "skip the loop". Routes through the per-model SKILL.md for action specifics and through `tao-launch-workflow` for platform/credentials/dataset intake.sentry-debug-issuegetsentry1.6KDebug and fix a Sentry issue — find it (by link, ID, or search), pull full context (stack trace, breadcrumbs, trace, logs), optionally run Seer root-cause / autofix, apply the code fix, and resolve it via a `Fixes PROJECT-NAME-12A` commit/PR. Use when working a known error or hunting one down to fix.n8n-error-handling-officialn8n-io1.6KUse when building any webhook-triggered workflow, scheduled/production-bound workflow, wiring a per-node error output, or any workflow where silent failure would drop user-visible work. Triggers on "webhook", "respond to webhook", "API", "production", "error", "failure", "5xx", "try/catch", "error workflow", "onError", "continueErrorOutput", "error branch", "node error output", "output(1)", "main[1]", "scheduled", or any workflow that runs unattended.tao-train-bevfusionnvidia1.6KBEVFusion for multi-sensor 3D object detection. Fuses LiDAR point clouds and camera images in bird's-eye-view (BEV) space, used in autonomous driving for robust 3D perception. Use when training, evaluating, or running inference for a TAO BEVFusion model. Trigger phrases include "train BEVFusion", "LiDAR + camera fusion", "BEV 3D detection", "multi-sensor 3D perception".tao-train-ocdnetnvidia1.6KOCDNet for scene text detection. Detects arbitrary-oriented text regions in natural images using a differentiable binarization approach. Use when training, evaluating, exporting, pruning, quantizing, retraining, or running inference for a TAO OCDNet model. Trigger phrases include "train OCDNet", "scene text detection", "arbitrary-oriented text boxes", "differentiable binarization detector".tao-train-oneformernvidia1.6KOneFormer for universal image segmentation. Unifies panoptic, instance, and semantic segmentation with a single architecture using task-conditioned queries. Use when training, evaluating, exporting, quantizing, or running inference for a TAO OneFormer model. Trigger phrases include "train OneFormer", "universal segmentation", "task-conditioned segmentation", "panoptic / instance / semantic in one model".r3f-animationenzed1.6KAnimate React Three Fiber objects with useFrame, damping, and GLTF clips. Use for procedural motion, animation transitions, or demand-loop animation; use physics guidance for collision-driven movement.synthetic-monitoring-checksgrafana1.6KAuthor Grafana Cloud Synthetic Monitoring checks, with deep coverage of k6 scripted and browser checks: SM's single-VU/single-iteration execution model, assertions that actually fail probe_success (expect() and fail() vs bare check()), secrets, deterministic scripts, robust browser locators, local validation with k6 run, deployment via UI/API/Terraform, verifying probe_success, and rollback. Also helps choose the simplest sufficient check type (HTTP/ping/DNS/TCP, MultiHTTP, scripted, browser). Utao-train-mask-grounding-dinonvidia1.6KMask Grounding DINO for grounded instance segmentation. Extends Grounding DINO with a mask-prediction head for open-set segmentation guided by text prompts. Use when training, evaluating, exporting, quantizing, or running inference for a TAO Mask-Grounding-DINO model. Trigger phrases include "train Mask Grounding DINO", "open-vocabulary segmentation", "text-prompted instance segmentation", "grounded mask DETR".firebasesickn331.6KFirebase gives you a complete backend in minutes - auth, database, storage, functions, hosting. But the ease of setup hides real complexity. Security rules are your last line of defense, and they're often wrong.bib-search-citationbahayonghang1.6KSearch and cite from local BibTeX/BibLaTeX .bib libraries, including Zotero exports. Use to find, filter, preview, export, or generate LaTeX/Typst citation snippets by topic, author, year, venue, DOI, arXiv ID, keywords, abstract, fields, recency, or claim support. Do not use for manuscript writing or polishing.survey-generationlingzhi2271.6KGenerate complete academic survey papers using multi-LLM parallel outline generation, RAG-based subsection writing, citation validation, and local coherence enhancement. Based on AutoSurvey pipeline. Use for writing comprehensive literature surveys.tao-validate-dataset-formatnvidia1.6KRun `tao-daft validate` to check NVIDIA TAO DAFT datasets for structure, schema, and cross-reference errors. Do not use for non-DAFT formats. Use when the user asks to validate a DAFT dataset, check DAFT schema, validate a TAO dataset format, or run `tao-daft validate`.release-managementrecoupable1.6KManage music releases using RELEASE.md documents stored in releases/{release-slug}/ within an artist workspace. Triggers when the user mentions an artist's album, EP, single, or project — or asks about release planning, DSP pitches, metadata, marketing, press materials, physical production, or tour coordination. First infer which artist and release the user means, then find or create the RELEASE.md. Use this skill to create, update, or pull data from release documents, and to generate deliverablimprove-appwondelai1.6KGuided journey from a shipped app that works but feels rough to a product that fits the job, flows without friction, reads clearly, and persuades honestly. Orchestrates nine skills phase by phase - jobs-to-be-done, ux-heuristics, design-everyday-things, refactoring-ui, microinteractions, made-to-stick, influence-psychology, high-perf-browser, steve-jobs-design-review - asking the user questions at every decision point and recording results in the project docs/ folder (CUSTOMER.md, DESIGN.md, POSseoul-weather-risknomadamas1.6K서울 행정동 이름을 정식명 우선·허용된 결정적 표기 별칭만으로 정규 place_id로 해석해 ASK 서울의 장소별 기상 위험 예상 시간대(weather_place_risk_window) 단일 제품을 hosted k-skill proxy에서 읽기 전용 조회한다. 사용자 API Key와 place_id 입력은 필요하지 않다.tilegym-monkey-patch-kernels-to-transformersnvidia1.6KIntegrate TileGym kernels into Hugging Face `transformers` models by replacing the library's submodule(s) and certain class(es)' implementations, and patching certain class(es)' init/forward/load weight methods prior to instantiating models. Used when the user requires integrating TileGym kernels into `transformers` models.information-architectureowl-listener1.6KDesign content structure, hierarchy, labelling, and the navigation model. Use when organising what exists. For the UI that exposes it use `navigation-patterns` (interaction-design); for user-generated grouping evidence use `card-sort-analysis` (design-research).neobrutalismbergside1.6KModern take on brutalism with bold borders, vivid accent colors, and raw, high-contrast layouts on warm surfaces.shadcnbergside1.6KShadcn/ui-inspired design with minimal, clean components, monochrome palette, and utility-first patterns.frontend-designcustomware-ai1.6KStrict frontend design guardrails for building modern, minimal-visual-noise, airy, non-generic app UIs. Use whenever creating or changing frontend UI, React components, shadcn/ui themes, Tailwind styles, app layouts, or first-version product screens. This skill complements vertical/domain skills like CPQ, CRM, and similar app builders: follow the selected domain skill's workflow and layout requirements, then enforce this skill's shared visual rules for brand-aware theming, generous spacing, typotao-train-deformable-detrnvidia1.6KDeformable DETR for 2D object detection. Uses deformable attention for efficient multi-scale feature processing, lighter than DINO with competitive accuracy. Use when training, evaluating, exporting, quantizing, or running inference for a TAO Deformable-DETR model. Trigger phrases include "train deformable-detr", "Deformable DETR object detection", "lightweight DETR detector".desktop-commander-overviewcline1.6KUse for Desktop Commander MCP capabilities — persistent shells and REPLs, long-running processes, filesystem beyond the workspace, structured files (.xlsx, .docx, .pdf, images) and large local data files such as CSVs, ripgrep search at scale, SSH, or cross-turn state.file-storagetigrisdata1.6KUse when working with Tigris file storage - uploading, downloading, deleting, listing files, presigned URLs, client uploads, or setting up Tigris CLI and SDK. Covers Next.js, Remix, Express, Rails, and Laravel. For Python/Django, see the tigris-python-sdk skill.upstash-qstash-jsupstash1.6KWork with the @upstash/qstash TypeScript/JavaScript SDK, an HTTP-based message queue, task scheduler, and background job system for serverless and edge runtimes (Next.js, Vercel, Cloudflare Workers, Deno, Node.js). Use when publishing messages to HTTP endpoints or URL groups, running background jobs without a long-running worker process, scheduling with cron expressions, delaying messages, building FIFO queues with parallelism and flow control, configuring retries and callbacks, handling a dead build-mvpbuildgreatproducts1.6KUse inside a product repository when the user wants the full MVP built from their BuilderOS spec documents. Triggers on phrases like "build my MVP", "build the app", "execute the roadmap", "start the build", "work through the whole roadmap", "build everything", or any request to implement the entire plan rather than a single task or phase. Requires `docs/prd.md` and `docs/product-roadmap.md` (plus `docs/product-vision.md` and `docs/design.md` for context). Works through every roadmap task in ordtao-run-on-slurmnvidia1.6KRemote SLURM GPU cluster execution over SSH with sbatch/srun, Pyxis/Enroot containers, and Lustre-backed results. Use when running TAO training/eval/inference jobs on an on-prem or DGX SLURM cluster. Trigger phrases include "run on SLURM", "submit sbatch", "DGX SLURM cluster", "Pyxis/Enroot container", "Lustre dataset".flows-code-reviewcognitedata1.6KRun the technical (code) review step of Flows app certification in a local git app. Loads flows-review-checks for the actual bar, then writes artifacts under reviews/code-review/feedback-round-<N>/. Use when the user asks for a Flows code review, technical review, pre-submit review, app certification code review, or "run flows-code-review". Re-run until 0 open Must Fix items remain before moving on to flows-design-review.bulk-operationshubspot1.6KFoundation patterns for the `hubspot` CLI — JSONL piping, batch read, pagination, dry-run/digest/confirm for destructive ops, and `hubspot history` for recovery. Every other skill builds on this one.crm-data-qualityhubspot1.6KFind incomplete records, normalize field values in bulk, dedupe with `hubspot objects merge`, and audit custom properties. Builds on `bulk-operations` for JSONL piping and dry-run/digest/confirm.minimax-music-genminimax-ai1.6KUse when user wants to generate music, songs, or audio tracks. Triggers on any request involving music creation, song writing, lyrics generation, audio production, or covers. Also triggers when user provides lyrics and wants them turned into a song, or describes a mood/scene and wants background music. Supports multilingual triggers — match equivalent phrases in any language. Do NOT use for music playback of existing files, music theory questions, or music recommendation without generation.tao-mine-aoi-imagesnvidia1.6KRuns the DEFT embed-then-mine workflow for VCN AOI iterations — embeds the gap-analysis target parquet, embeds a source pool, and mines nearest-neighbour source images for downstream augmentation. Use as the immediate next step after `tao-route-visual-changenet-samples` when expanding a real-image augmentation queue from the mining subset.tao-train-fast-foundation-stereonvidia1.6KReal-time stereo depth estimation using FastFoundationStereo (FFS), the distilled bp2 commercial variant of FoundationStereo. Predicts disparity maps from stereo image pairs with ~10× lower latency than full FoundationStereo. Use when training, evaluating, exporting, or running inference for a TAO FastFoundationStereo (FFS) model. Trigger phrases include "train fast stereo", "real-time stereo disparity", "FastFoundationStereo", "distilled stereo depth".tao-train-foundation-stereonvidia1.6KStereo depth estimation using FoundationStereo. Predicts disparity maps from stereo image pairs for 3D reconstruction. Use when training, evaluating, exporting, or running inference for a TAO FoundationStereo model. Trigger phrases include "train stereo depth", "FoundationStereo", "stereo disparity estimation", "3D reconstruction from stereo".tao-train-sparse4dnvidia1.6KSparse4D for multi-camera temporal 3D object detection and tracking. Uses sparse queries with deformable attention across camera views and time for end-to-end 3D perception, with an instance bank for temporal tracking. Use when training, evaluating, exporting, quantizing, or running inference for a TAO Sparse4D model. Trigger phrases include "train Sparse4D", "multi-camera 3D detection", "temporal 3D tracker", "sparse query 3D perception".appwrite-typescriptappwrite1.6KAppwrite TypeScript SDK skill. Use when building browser-based JavaScript/TypeScript apps, React Native mobile apps, or server-side Node.js/Deno backends with Appwrite. Covers client-side auth (email, OAuth, anonymous), database queries, file uploads, real-time subscriptions, and server-side admin via API keys for user management, database administration, storage, and functions.