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Found 365 Skills
Blockchain analytics via Dune REST API — execute DuneSQL queries against live on-chain data, discover decoded contract tables, and monitor credit usage. Use when the user asks about on-chain data, wallet activity, DEX trades, token transfers, smart contract events, or says "query Dune", "run a Dune query", or "search Dune datasets". Pairs with MoonPay to analyze wallets you create and fund.
Finds and inspects data assets within Google Cloud. Relevant when any of the following conditions are true: 1. The user request involves finding, exploring, or inspecting data assets in Google Cloud, such as: - BigQuery datasets, tables, or views - BigLake catalog or tables - Spanner instances, databases or tables - etc. 2. You need to retrieve the schema, metadata, or governance policies for a GCP data asset. 3. You have a keyword or topic (e.g., "sales data") but lack the specific table or resource ID. 4. You are attempting to find data using `bq ls`, as this skill offers a superior approach. Don't use when: - Assets are outside Google Cloud
Use when the user asks for nearby public/open restrooms or 근처 화장실. Always ask the user's current location first, then use the official nationwide public-restroom standard dataset plus Kakao anchor resolution.
Build headless data tables with TanStack Table v8. Server-side pagination, filtering, sorting, and virtualization for Cloudflare Workers + D1. Prevents 12 documented errors. Use when building tables with large datasets, coordinating with TanStack Query, or fixing state management, performance, or React 19+ compatibility issues.
End-to-end epidemiological data analysis — from research question to statistical report. Covers study design assessment, dataset discovery and download, data wrangling, confounder adjustment, regression modeling, sensitivity analysis, visualization, and biological interpretation. Integrates ToolUniverse tools for dataset discovery, literature search, and biological context with Python code execution for data analysis. Use whenever users ask to analyze health data, study disease risk factors, assess exposure-outcome relationships, or conduct observational epidemiology. Also use when users want to run regression on clinical/survey data, calculate odds ratios or hazard ratios from a dataset, adjust for confounders, or produce a Table 1. If the task involves downloading a health dataset and running statistical analysis on it, this is the right skill.
Create effective data visualizations with Python (matplotlib, seaborn, plotly). Use when building charts, choosing the right chart type for a dataset, creating publication-quality figures, or applying design principles like accessibility and color theory.
Interact with Litefuse and access its documentation. Use when needing to (1) query or modify Litefuse data programmatically via the CLI — traces, prompts, datasets, scores, sessions, and any other API resource, (2) look up Litefuse documentation, concepts, integration guides, or SDK usage, or (3) understand how any Litefuse feature works. This skill covers CLI-based API access (via npx) and multiple documentation retrieval methods.
Implement and configure Syncfusion MultiColumnComboBox control in Windows Forms - an advanced combobox with multiple columns in dropdown and virtual data binding for large datasets. Use when creating dropdown lists with multiple data fields, DataSource binding, DisplayMember/ValueMember configuration, or column headers in dropdown. Covers filtered dropdown lists and replacing standard ComboBox with multi-column alternatives.
Generates comprehensive synthetic fine-tuning datasets in ChatML format (JSONL) for use with Unsloth, Axolotl, and similar training frameworks. Gathers requirements, creates datasets with diverse examples, validates quality, and provides framework integration guidance.
Complete the full loop of "Data → Fine-tuning Training → Export → Deployment → Inference" using Bailian CLI (`bl`), or deploy base models directly without training. Supports fine-tuning of text models (SFT/DPO/CPT), audio TTS models (CosyVoice), and image generation models (Wan2.7). Covers dataset validation/upload, creating fine-tuning tasks, waiting for training completion, exporting the best checkpoint, creating inference deployments, waiting for readiness, and providing inference examples. This skill should be activated when users mention actions like "training models", "fine-tuning", "fine-tune", "finetune", "deploying models", "model launch", "running/calling fine-tuned models", "training an inference model", "continuing pre-training", "LoRA/SFT/DPO training", "speech synthesis models", "TTS fine-tuning", "CosyVoice", "voice cloning", "image generation fine-tuning", "text-to-image", "image-to-image", "Wan2.7", "image model training" on Bailian / DashScope / Alibaba Cloud Model Studio — even if users don't explicitly mention "using bl", as long as the intention is training or deployment on the Bailian platform, use this skill and do not assemble commands on your own.
Access NCBI GEO for gene expression/genomics data. Search/download microarray and RNA-seq datasets (GSE, GSM, GPL), retrieve SOFT/Matrix files, for transcriptomics and expression analysis.
Use Fabric CLI for Power BI operations — semantic models, reports, DAX queries, refresh, gateways. Activate when users work with Power BI items, need to refresh datasets, execute DAX, manage reports, or troubleshoot refresh failures.