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Found 1,913 Skills
Verify code against paper. Use when user asks "does this match the paper", "check my implementation", or is implementing equations/algorithms from literature.
Financial Data Analysis Skill (based on `bl mcp` + Alibaba Cloud Bailian MCP Market `market-cmapi00073529`), covering financial instruments such as China A-shares, funds, and bonds. It supports stock screening, fund screening, fund manager screening, financial data query (net profit / revenue / ROE, etc.), macro and industry time-series data (GDP / CPI / production-sales-price), brokerage research report retrieval, and A-share listed company announcement retrieval. Be sure to activate when users ask about the following keywords: stock selection / stock screening, fund screening, fund manager screening, financial data / net profit / revenue / valuation, macroeconomy / GDP / CPI, industry production-sales-price, brokerage research report / industry research report, listed company announcement. Not applicable to: general programming issues, non-financial data, non-Chinese market instruments.
OneFormer 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".
Monocular depth estimation using Metric Depth Anything v2 or Relative Depth Anything architectures. Predicts per-pixel depth from single RGB images. Use when training, evaluating, exporting, or running inference for a TAO monocular depth model. Trigger phrases include "train monocular depth", "DepthAnything v2", "metric depth from single image", "monocular depth estimation".
OCDNet 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".
Mask 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".
MAL (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".
Assess if IDD fits your project and learn about Intent-Driven Development. Use /intent-assess to evaluate project suitability or /intent-assess --learn for IDD education.
Use this skill when users need to stress test their business model, identify scale limitations, find bottlenecks, determine if they're trading time for money, or evaluate unit economics. Activates for "can this scale," "what breaks at 10x," or business model viability questions.
Expert Spring Boot 4 testing specialist that selects the best Spring Boot testing techniques for your situation with Junit 6 and AssertJ.
Use when investigating why something happened and need to distinguish correlation from causation, identify root causes vs symptoms, test competing hypotheses, control for confounding variables, or design experiments to validate causal claims. Invoke when debugging systems, analyzing failures, researching health outcomes, evaluating policy impacts, or when user mentions root cause, causal chain, confounding, spurious correlation, or asks "why did this really happen?"
Audit code architecture for over-engineering and unnecessary abstractions. Use when user asks to "review architecture", "simplify code structure", "reduce over-engineering", "evaluate abstractions", or mentions premature abstraction, interface proliferation, factory patterns, YAGNI, or enterprise-grade complexity.