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# Skill 仓库 描述 安装量
9851 powerpoint-ppt practicalswan/agent-skills
PowerPoint Presentation Workflows Tech Stack Target / Version: PowerPoint current desktop or web releases and python-pptx automation. Use this skill when a .pptx deck is the output and slide composition matters. Leverage native parallel subagent dispatch and 200k+ context windows where available. Current MCP Reality Presentation MCP tooling is host-dependent. Some clients expose Office presentation tools directly, while others do not. Do not assume stable public tool names. If the current client...
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9852 day1-onboarding ai-native-camp/camp-2
Day 1: Onboarding 이 스킬이 호출되면 아래 STOP PROTOCOL 을 반드시 따른다. STOP PROTOCOL — 절대 위반 금지 이 프로토콜은 이 스킬의 최우선 규칙이다. 아래 규칙을 위반하면 수업이 망가진다. 각 블록은 반드시 2턴에 걸쳐 진행한다 ┌─ Phase A (첫 번째 턴) ──────────────────────────────┐ │ 1. references/에서 해당 블록 파일의 EXPLAIN 섹션을 읽는다 │ │ 2. 기능을 설명한다 │ │ 3. references/에서 해당 블록 파일의 EXECUTE 섹션을 읽는다 │ │ 4. "지금 직접 실행해보세요"라고 안내한다 │ │ 5. ⛔ 여기서 반드시 STOP. 턴을 종료한다. │ │ ...
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9853 adk-frontend botpress/skills
No SKILL.md available for this skill. View on GitHub
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9854 tao-run-on-kubernetes nvidia/skills
Kubernetes Submits TAO container jobs as Kubernetes Jobs. Works on any cluster reachable via kubeconfig (EKS / GKE / AKS / on-prem) or in-cluster service account (when the SDK runs inside a pod). Single-pod by default; opt into multi-node distributed training via num_nodes > 1 (uses Indexed Job + headless Service, see Multi-node training below). Preflight Four checks: GPU host runtime ready, SDK installed, cluster reachable, GPU Operator/device plugin present. 0. GPU node host runtime. Run thi...
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9855 tao-train-optical-inspection nvidia/skills
Optical Inspection Optical inspection for defect detection using Siamese networks. Compares image pairs to detect manufacturing defects, anomalies, or quality issues. Set train.pretrained_model_path for pretrained Siamese weights. For TAO Deploy TensorRT actions ( gen_trt_engine , TensorRT evaluate , and TensorRT inference ), read references/tao-deploy-optical-inspection.md first. The parent PyT container does not expose optical_inspection gen_trt_engine ; TensorRT engine generation is deploy-on...
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9856 tao-generate-image-grounding nvidia/skills
Image Grounding Pipeline Turn (image, caption) pairs into per-image grounded annotations: cleaned captions, referring expressions with character spans, and pixel-space bounding boxes for each expression. A single VLM (Gemini or any OpenAI-compatible endpoint) handles both steps. Purpose Generate phrase-grounded training data for referring-expression and grounding models. The VLM acts as a "teacher" annotator: Step 0 extracts referring expressions from the caption while looking at the image; Step...
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9857 tao-analyze-changenet-rca nvidia/skills
TAO ChangeNet Classification RCA Skill You are an expert investigator for NVIDIA TAO Visual ChangeNet classification experiments. Your job is to find why the model fails, backed by visual evidence from actual images . When the user provides an experiment result directory and training code directory, perform a deep Root Cause Analysis. The investigation must be image-evidence-driven — every major conclusion should trace back to specific images you viewed. Inputs Experiment result directory — cont...
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9858 tao-train-action-recognition nvidia/skills
Action Recognition Action recognition from video sequences. Supports RGB, optical flow, and joint (multi-stream) input types for classifying temporal actions in video clips. Set model.pretrained_model_path for pretrained backbone weights. Dataclass Schemas Generated TAO Core schemas are packaged in schemas/<action>.schema.json , with schemas/manifest.json listing available actions. Each generated schema also emits references/spec_template_<action>.yaml from the schema top-level default field. Au...
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9859 tao-run-inference-service nvidia/skills
TAO Inference Microservice Instructions To start an inference service: Collect required inputs (Section 1) and resolve the container image (Section 2). Build the job payload and inner command (Sections 3–4.1); use references/code-templates.yaml → job_payload_builder . Read skills/platform/<platform>/SKILL.md and start the container (Section 4.2). Write the service registry and poll readiness (Section 4.3); use references/code-templates.yaml → registry_write.<platform> and readiness_check . To se...
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9860 tao-train-grounding-dino nvidia/skills
Grounding DINO Grounding DINO for open-set object detection. Combines DINO-style detection with BERT text encoder for language-guided detection. Detects objects described by text prompts without fixed class vocabulary. Set train.pretrained_model_path for full Grounding DINO weights or model.pretrained_backbone_path for backbone-only. For TAO Deploy TensorRT actions ( gen_trt_engine , TensorRT evaluate , and TensorRT inference ), read references/tao-deploy-grounding-dino.md first. Deploy spec tem...
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9861 framer-motion dylantarre/animation-principles
Framer Motion / Motion Animation Guidelines You are an expert in Framer Motion (now Motion), React, and TypeScript. Follow these guidelines when creating animations. Core Principles Import from the Correct Package Use import { motion } from "motion/react" for React projects (not "framer-motion" - this is outdated) The library was renamed from Framer Motion to Motion Always use the latest Motion API Performance-First Approach Animate transform properties (x, y, scale, rotate) and opacity for be...
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9862 funding-digest anthropics/financial-services
AI DISCLAIMER (MANDATORY): You MUST include the following disclaimer text in the powerpoint footer. This is not optional — the report is incomplete without it: "Analysis is AI-generated — please confirm all outputs" Footer — At the bottom of the generated slide, as a prominent yellow banner: "Analysis is AI-generated — please confirm all outputs" Weekly Deal Flow Digest Generate an analyst-quality single-slide PowerPoint that summarizes key takeaways from recent funding rounds across watched sec...
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9863 tao-train-nvpanoptix3d nvidia/skills
NVPanoptix3D NVPanoptix3D for panoptic 3D scene reconstruction from posed RGB images. Produces 3D panoptic segmentation (semantic, instance, and panoptic masks) with occupancy completion. Built on VGGT backbone with Mask2Former-style head and 3D frustum reconstruction. Uses 2D and 3D stage checkpoints. Set train.checkpoint_2d and train.checkpoint_3d for staged initialization. Dataclass Schemas Generated TAO Core schemas are packaged in schemas/<action>.schema.json , with schemas/manifest.json li...
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9864 fsi-strip-profile anthropics/financial-services
Workflow 1. Clarify Requirements Ask the user : Single-slide or multi-slide (3-4 slides)? Ask the user : Any specific focus areas or topics to emphasize? Only after user confirms , proceed to research 2. Research & Planning Data Sources: Primary : Company filings (BamSEC, SEC EDGAR - "Item 1. Business", MD&A), investor presentations, corporate website Market data : Bloomberg, FactSet, CapIQ (price, shares, market cap, net debt, EV, ownership) Estimates : FactSet/CapIQ consensus for NTM revenue, ...
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9865 qdrant-performance-optimization qdrant/skills
Qdrant Performance Optimization There are different aspects of Qdrant performance, this document serves as a navigation hub for different aspects of performance optimization in Qdrant. Search Speed Optimization There are two different criteria for search speed: latency and throughput. Latency is the time it takes to get a response for a single query, while throughput is the number of queries that can be processed in a given time frame. Depending on your use case, you may want to optimize for one...
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9866 tao-analyze-gaps-visual-changenet nvidia/skills
TAO VCN Classify Gap Analysis Skill You are an analyst for NVIDIA TAO VCN Classify (Visual Component Net) inference results. Your job is to identify the weakest samples per ground-truth label by measuring signed distance from the decision threshold in the wrong direction , then surface them for downstream augmentation or relabeling. This skill is intentionally lightweight. VCN's classify head is a single-score binary boundary (PASS vs NO_PASS by siamese_score ), so the analysis is computational,...
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9867 tao-train-pose-classification nvidia/skills
Pose Classification Pose classification using ST-GCN (Spatial Temporal Graph Convolutional Network). Classifies skeleton sequences into action categories from pose keypoint data. Typically trained from scratch on skeleton data. The packaged PyTorch Pose Classification CLI supports dataset_convert , train , evaluate , export , and inference . dataset_convert is conditional: run it only when the input is raw DeepStream BodyPose JSON. If the dataset is already converted to TAO-ready .npy / .pkl fil...
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9868 telegram-reader himself65/finance-skills
Telegram News Skill (Read-Only) Reads Telegram channels and groups for financial news and market research using tdl , a Telegram CLI tool. This skill is read-only. It is designed for financial research: reading channel messages, monitoring financial news channels, and exporting message history. It does NOT support sending messages, joining/leaving channels, or any write operations. Step 1: Ensure tdl Is Installed Current environment status: !`(command -v tdl && tdl version 2>&1 | head -3 || echo...
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9869 build-loop-claude-code buildgreatproducts/builder-os
Claude Code Build Loop Quality-gated feature work: nothing ships on "it compiles" — every increment is built, reviewed, tested end to end, and fixed before the user hears "done." Source of work A plan file exists (roadmap, refactor plan, or task list with - [ ] checkboxes — search the repo): work the first unchecked task. Tasks are ordered intentionally — never skip ahead. If the plan references spec docs, read only the sections relevant to the current task. No plan (or the request is outside it...
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9870 tao-train-reid nvidia/skills
Re-Identification Person re-identification. Learns discriminative embeddings to match the same person across different camera views. Metric learning based. Set model.pretrained_model_path for pretrained weights. Dataclass Schemas Generated TAO Core schemas are packaged in schemas/<action>.schema.json , with schemas/manifest.json listing available actions. Each generated schema also emits references/spec_template_<action>.yaml from the schema top-level default field. AutoML enablement is declared...
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9871 tao-analyze-gaps-vlm-bcq nvidia/skills
VLM Binary Classification Gap Analysis Reads a VLM predictions JSON, compares each model response against ground truth, and writes FP/FN failure cases to a JSONL file with a summary report. Purpose After running a VLM on a binary yes/no evaluation task, the predictions need to be compared against ground truth to identify failure cases. This skill produces a structured list of FP (false positive) and FN (false negative) samples that downstream RCCA stages (e.g., cosmos generation, root cause anal...
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9872 tao-train-visual-changenet nvidia/skills
Visual ChangeNet Visual ChangeNet is a TAO Toolkit model for visual inspection and defect detection. It supports two tasks: Classify — Binary image classification using a siamese-style architecture with a shared backbone (C-RADIO ViT) and a learnable difference module. Compares image pairs to classify defects as PASS/NO_PASS. Segment — Pixel-level change segmentation using a ViT-Large NVDINOv2 backbone. Compares before/after image pairs to produce a binary change mask. The backbone weight ( c_ra...
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9873 tao-train-metric-learning-recognition nvidia/skills
ML Recog Metric learning recognition for fine-grained visual recognition. Learns embeddings for retrieval-based matching (e.g., retail product recognition). Uses triplet/contrastive losses. Set model.pretrained_model_path for pretrained backbone. For TAO Deploy TensorRT actions ( gen_trt_engine , TensorRT evaluate , and TensorRT inference ), read references/tao-deploy-metric-learning-recognition.md first. Deploy spec templates live in this skill's references/ folder with the spec_template_deploy...
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9874 tao-train-dino nvidia/skills
DINO DINO (DETR with Improved DeNoising Anchor Boxes) for 2D object detection. Transformer-based detector with denoising training, multi-scale features, and optional distillation support. Uses pretrained backbone weights (e.g. ResNet-50 ImageNet). Set model.pretrained_backbone_path for backbone-only or train.pretrained_model_path for full model. When To Use Train, evaluate, export, distill, quantize, or run inference for a TAO DINO 2D object detector. For TAO Deploy TensorRT actions ( gen_trt_en...
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9875 tao-train-depth-anything-v2 nvidia/skills
Depth Net Mono Monocular depth estimation using Metric Depth Anything v2 or Relative Depth Anything architectures. Predicts per-pixel depth from single RGB images. Pretrained checkpoint loading varies by model variant and use case — see the Pretrained checkpoint loading — use case matrix in references/parameters.md . The mono and stereo skills both invoke the unified TAO depth_net CLI inside the container; the mono/stereo family is selected via model.model_type (see references/parameters.md ). F...
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9876 tao-train-mask2former nvidia/skills
Mask2Former Mask2Former for universal image segmentation (panoptic, instance, and semantic). Transformer-based with masked attention for high-quality segmentation results. Set model.backbone.pretrained_weights for Swin backbone weights. For TAO Deploy TensorRT actions ( gen_trt_engine , TensorRT evaluate , and TensorRT inference ), read references/tao-deploy-mask2former.md first. Deploy spec templates live in this skill's references/ folder with the spec_template_deploy_*.yaml prefix. Dataclass ...
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9877 tao-train-nvdinov2 nvidia/skills
NVDINOv2 NVDINOv2 for self-supervised visual representation learning. Trains vision transformers via self-distillation (teacher-student) without labels. Produces general-purpose visual features. Set train.pretrained_model_path for pretrained ViT weights. For TAO Deploy TensorRT actions ( gen_trt_engine ), read references/tao-deploy-nvdinov2.md first. Deploy spec templates live in this skill's references/ folder with the spec_template_deploy_*.yaml prefix. Dataclass Schemas Generated TAO Core sch...
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9878 tao-train-mask-auto-encoder nvidia/skills
MAE MAE (Masked Autoencoder) for self-supervised pretraining and fine-tuning. Masks random patches and reconstructs them to learn visual representations. Supports pretrain and finetune stages. Set train.pretrained_model_path for pretrained MAE weights when fine-tuning. For TAO Deploy TensorRT actions ( gen_trt_engine ), read references/tao-deploy-mask-auto-encoder.md first. Deploy spec templates live in this skill's references/ folder with the spec_template_deploy_*.yaml prefix. The parent PyTor...
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9879 tao-train-rtdetr nvidia/skills
RT-DETR RT-DETR (Real-Time DEtection TRansformer) for 2D object detection. Designed for real-time inference with competitive accuracy. Supports distillation and quantization for deployment optimization. Set model.pretrained_backbone_path for backbone weights or train.pretrained_model_path for full model. For TAO Deploy TensorRT actions ( gen_trt_engine , TensorRT evaluate , and TensorRT inference ), read references/tao-deploy-rtdetr.md first. Deploy spec templates live in this skill's references...
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9880 gstack-workflow-assistant reason-machines/trending-skills
gstack Workflow Assistant Skill by ara.so — Daily 2026 Skills collection Transform Claude Code from a generic assistant into a team of specialists you can summon on demand. Eight opinionated workflow skills that act as CEO, Engineering Manager, Release Manager, and QA Engineer with slash commands for planning, review, shipping, and testing. What It Does gstack provides specialized AI personas and workflows: CEO Review : Rethink problems and find the 10-star product hiding in requests Engineering...
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9881 deepseek-ocr reason-machines/trending-skills
DeepSeek-OCR Skill by ara.so — Daily 2026 Skills collection. DeepSeek-OCR is a vision-language model for Optical Character Recognition with "Contexts Optical Compression." It supports native and dynamic resolutions, multiple prompt modes (document-to-markdown, free OCR, figure parsing, grounding), and can be run via vLLM (high-throughput) or HuggingFace Transformers. It processes images and PDFs, outputting structured text or markdown. Installation Prerequisites CUDA 11.8+, PyTorch 2.6.0 Python ...
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9882 autoresearchclaw-autonomous-research reason-machines/trending-skills
AutoResearchClaw — Autonomous Research Pipeline Skill by ara.so — Daily 2026 Skills collection. AutoResearchClaw is a fully autonomous 23-stage research pipeline that takes a natural language topic and produces a complete academic paper: real arXiv/Semantic Scholar citations, sandboxed experiments, statistical analysis, multi-agent peer review, and conference-ready LaTeX (NeurIPS/ICML/ICLR). No hallucinated references. No human babysitting. Installation Clone and install git clone https://githu...
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9883 wordpress-content jezweb/claude-skills
WordPress Content Create, update, and manage WordPress content — posts, pages, media, categories, tags, and menus. Produces live content on the site via WP-CLI or the REST API. Prerequisites Working WP-CLI SSH connection or REST API credentials (use wordpress-setup skill) Site config from wordpress.config.json or wp-cli.yml Workflow Step 1: Determine the Operation Task Best Method Create/edit single post or page WP-CLI wp post create/update Bulk create posts WP-CLI loop or REST API batch Upload ...
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9884 tao-run-automl-deft-pipeline nvidia/skills
AutoML + DEFT Pipeline A workflow-bridge skill that runs three phases in sequence by delegating to two existing skills — tao-run-automl for HPO and a DEFT application skill (default tao-run-deft-aoi for AOI; other skills/applications/deft-* skills for non-AOI cases) for the iterative data-improvement loop. This skill does not re-implement AutoML or DEFT. It owns only the connective tissue: HPO spec inputs, the spec-handoff between AutoML and DEFT, and the post-DEFT AutoML re-run on the augmented...
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9885 tao-run-deft-aoi nvidia/skills
Skill: tao-run-deft-aoi When to Use This Skill Use this skill when the user wants an agent to run the full DEFT AOI improvement loop for an NVIDIA TAO VisualChangeNet / ChangeNet PCB inspection model: baseline evaluation, RCA, synthetic defect generation, data mining, retraining, and deployment gating until a KPI target is met. "Run the DEFT loop" "Fine-tune until FAR below 0.1% at recall=100%" "Improve my AOI ChangeNet model using RCA and synthetic defects" "Iterate training until false accept ...
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9886 tao-run-platform nvidia/skills
TAO Execution SDK The SDK is the optional Python layer for users who need job handles, S3 I/O wrapping, or platform-specific features (SLURM/Lustre queues, Kubernetes Jobs, local Docker debugging, Brev instance reuse). Most TAO skills run with just docker run and don't need it. Reach for the SDK when: You want a Job handle to poll status and stream logs over time. You need S3-aware input download / output upload baked into the entrypoint. You're chaining multiple jobs and want persisted state. P...
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9887 tao-generate-referring-expressions nvidia/skills
Image Referring Expression Pipeline Generate referring-expression and grounding annotations from images with KITTI-format bounding box labels. A single VLM (Gemini or any OpenAI-compatible endpoint) runs four steps: per-object region descriptions, holistic image captions, grouped grounding expressions tied to bboxes, and an optional double-check verification pass. Purpose Transform (image, KITTI labels) pairs into a unified annotations.jsonl containing rich, grounded referring expressions. The V...
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9888 tao-train-centerpose nvidia/skills
CenterPose CenterPose for keypoint / pose estimation. Detects object centers and regresses keypoint locations. Used for 6-DoF object pose estimation. Set model.backbone.pretrained_backbone_path. For TAO Deploy TensorRT actions ( gen_trt_engine , TensorRT evaluate , and TensorRT inference ), use the deploy spec templates packaged in this skill's references/ folder with the spec_template_deploy_*.yaml prefix. Dataclass Schemas Generated TAO Core schemas are packaged in schemas/<action>.schema.json...
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9889 tao-train-mask-auto-label nvidia/skills
MAL MAL (Mask Auto-Label) for weakly-supervised segmentation. Produces segmentation masks from minimal annotations (e.g., point or box annotations). Uses ViT-MAE backbone. Set train.pretrained_model_path for ViT-MAE pretrained weights. Dataclass Schemas Generated TAO Core schemas are packaged in schemas/<action>.schema.json , with schemas/manifest.json listing available actions. Each generated schema also emits references/spec_template_<action>.yaml from the schema top-level default field. AutoM...
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9890 tao-train-single-step nvidia/skills
Normal Train Standard supervised fine-tuning: train a model on a labeled dataset, optionally evaluate, then optionally export. The most common TAO workflow for adapting a pretrained model to a new dataset. Steps train — executed through AutoML when the selected model has automl_enabled: true and automl_policy is on ; set automl_policy=off for a plain single training run eval — executed if eval_dataset_uri is resolved export — optional, on user request after training Prerequisites Show more Insta...
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9891 ib-check-deck anthropics/financial-services
IB Deck Checker Perform comprehensive QC on the presentation across four dimensions. Read every slide, then report findings. Environment check This skill works in both the PowerPoint add-in and chat. Identify which you're in before starting: Add-in — read from the live open deck. Chat — read from the uploaded .pptx file. This is read-and-report only — no edits — so the workflow is identical in both. Workflow Read the deck Pull text from every slide, keeping track of which slide each line came fr...
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9892 skill-creator anthropics/financial-services
Skill Creator A skill for creating new skills and iteratively improving them. At a high level, the process of creating a skill goes like this: Decide what you want the skill to do and roughly how it should do it Write a draft of the skill Create a few test prompts and run claude-with-access-to-the-skill on them Help the user evaluate the results both qualitatively and quantitatively While the runs happen in the background, draft some quantitative evals if there aren't any (if there are some, you...
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9893 adk-evals botpress/skills
ADK Evals Skill What are Evals? Evals are automated conversation tests for ADK agents. Each eval defines a scenario — a sequence of user messages or events — and asserts on what the bot should do: what it says, which tools it calls, how state changes, which workflows run, and more. Evals run against a live dev bot ( adk dev ), so they test the full stack — not mocks. When to Use This Skill Use this skill when the developer asks about: Writing evals — file format, assertions, turn types, setup Ru...
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9894 tao-train-pointpillars nvidia/skills
PointPillars PointPillars for 3D object detection from LiDAR point clouds. Encodes point clouds into a pseudo-image via pillar-based representation, then applies 2D detection. Used in autonomous driving / robotics. Typically trained from scratch. Provide train.resume_training_checkpoint_path to resume. For TAO Deploy TensorRT actions ( gen_trt_engine , TensorRT evaluate , and TensorRT inference ), read references/tao-deploy-pointpillars.md first. Deploy spec templates live in this skill's refere...
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9895 tao-train-bevfusion nvidia/skills
BEVFusion BEVFusion 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. Set pretrained backbone paths for Swin image backbone. BEVFusion requires the BEVFusion-specific TAO container nvcr.io/nvidia/tao/tao-toolkit:5.5.0-pyt . The shared TAO PyTorch 7.0 RC image does not package mmdet3d and fails before any BEVFusion action can parse its spec. The model-skill action is named dataset_c...
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9896 tao-train-mask-grounding-dino nvidia/skills
Mask Grounding DINO Mask Grounding DINO for grounded instance segmentation. Extends Grounding DINO with mask prediction head for open-set segmentation guided by text prompts. Set train.pretrained_model_path for full model weights. For TAO Deploy TensorRT actions ( gen_trt_engine , TensorRT evaluate , and TensorRT inference ), read references/tao-deploy-mask-grounding-dino.md first. Deploy spec templates live in this skill's references/ folder with the spec_template_deploy_*.yaml prefix. Dataclas...
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9897 swap-curve-strategy anthropics/financial-services
Swap Curve Strategy Analysis You are an expert rates strategist specializing in swap curve analysis. Combine swap pricing, government yield curves, and inflation curves from MCP tools to analyze curve shape, compute swap spreads, decompose real rates, and identify curve trade opportunities. Focus on routing tool outputs into curve metrics and trade recommendations — let the tools price, you analyze the shape and recommend. Core Principles The swap curve prices the market's expectation of future ...
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9898 deck-refresh anthropics/financial-services
Deck Refresh Update numbers across the deck. The deck is the source of truth for formatting; you're only changing values. Environment check This skill works in both the PowerPoint add-in and chat. Identify which you're in before starting — the edit mechanism differs, the intent doesn't: Add-in — the deck is open live; edit text runs, table cells, and chart data directly. Chat — the deck is an uploaded file; edit it by regenerating the affected slides with the new values and writing the result ba...
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9899 tao-run-on-brev nvidia/skills
Brev NVIDIA Brev provides on-demand GPU instances across multiple cloud providers. Instances come pre-loaded with NVIDIA drivers, CUDA, Docker, and NVIDIA Container Toolkit. Brev is instance-based (not job-based). You create an instance, run commands on it via brev exec , and delete it when done. The TAO SDK's BrevHandler wraps this into the standard job interface. Preflight This skill needs the brev CLI and an active login. Check before proceeding: 1. brev CLI installed command -v brev > /dev/...
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9900 tao-train-ocdnet nvidia/skills
OCDNet OCDNet for scene text detection. Detects arbitrary-oriented text regions in natural images using a differentiable binarization approach. Set model.pretrained_model_path for pretrained weights. For TAO Deploy TensorRT actions ( gen_trt_engine , TensorRT evaluate , and TensorRT inference ), read references/tao-deploy-ocdnet.md first. Deploy spec templates live in this skill's references/ folder with the spec_template_deploy_*.yaml prefix. The PyT OCDNet CLI supports train , evaluate , expor...
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