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Credit risk data cleaning and variable screening pipeline for pre-loan modeling. Use when working with raw credit data that needs quality assessment, missing value analysis, or variable selection before modeling. it covers data loading and formatting, abnormal period filtering, missing rate calculation, high-missing variable removal,low-IV variable filtering, high-PSI variable removal, Null Importance denoising, high-correlation variable removal, and cleaning report generation. Applicable scenarios arecredit risk data cleaning, variable screening, pre-loan modeling preprocessing.

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Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub. Use when: handling authentication; managing local cache; managing Hugging Face Buckets; running or scheduling jobs on Hugging Face infrastructure; managing Hugging Face repos; discussions and pull requests; browsing models, datasets and spaces; reading, searching, or browsing academic papers; managing collections; querying datasets; configuring spaces; setting up webhooks; or deploying and managing HF Inference Endpoints. Make sure to use this skill whenever the user mentions 'hf', 'huggingface', 'Hugging Face', 'huggingface-cli', or 'hugging face cli', or wants to do anything related to the Hugging Face ecosystem and to AI and ML in general. Also use for cloud storage needs like training checkpoints, data pipelines, or agent traces. Use even if the user doesn't explicitly ask for a CLI command. Replaces the deprecated `huggingface-cli`.

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Measure page loading speed and identify what prevents a page from loading in under three seconds. Use performance measurements to guide improvements such as lazy loading, caching, CDN delivery, and reducing resource costs.

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• Investigating slow page loads
• Finding heavy resources and costly rendering steps
• Checking performance on a throttled 3G connection

Find CSS and JavaScript that delay a page’s first visible content. Confirm the bottleneck with browser tools or performance data, then adjust loading behavior and inline essential styles to help the page start rendering sooner.

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• Investigating a blank screen during page loading
• Reviewing CSS and JavaScript loading behavior
• Inlining styles needed for the initial display

Review slow page loads and choose resource hints, browser instructions that start loading or connecting earlier. Use measurements to identify bottlenecks, then recommend preload, preconnect, prefetch, or dns-prefetch for important assets and likely next-page resources.

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• Reviewing slow loading of prominent images and fonts
• Preparing connections to external services
• Prefetching resources for likely next-page visits

Build and check clinical machine learning workflows with PyHealth, from loading electronic health records, signals, or images to training and evaluation. Includes patient-level data splits, prediction task checks, model checkpoints, and medical code mapping.

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• Prototype mortality and readmission prediction models
• Check patient splits and data leakage
• Train and evaluate sleep staging models

Write, review, or refactor React code using prioritized guidance for data fetching, bundle size, rendering, component structure, testing, and type safety. Start with high-impact issues such as sequential requests and unnecessary library loading.

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• Writing React components and data-fetching logic
• Reviewing code for loading and rendering performance
• Refactoring large components and overly broad interfaces

Build multi-page Next.js applications from JSON specifications. This skill guides route setup, shared layouts, page metadata, and server-side rendering, which prepares pages on the server, with optional data loading before display.

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• Build a multi-page app from JSON specifications
• Share navigation and layouts across pages
• Load server data before rendering a page

Turn Stitch designs into React and Vite dashboards with reusable components and asynchronous data fetching. It applies shared design settings from DESIGN.md, includes accessibility checks, and supports optional blockchain data reads.

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• Build a React dashboard from a Stitch screen
• Apply shared design settings from DESIGN.md
• Add data fetching and loading states

Create a temporary workbench for one existing component, using realistic mock data and a grouped state switcher. View loading, empty, error, access, and other implemented states individually, with a link to each state.

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• Comparing loading, empty, and error states in a table
• Checking displays for different roles and plans
• Inspecting layouts with realistic amounts of sample data

Build dashboard panels in vanilla TypeScript with resizing, saved layout state, loading indicators, and retry controls. Examples also show how to wrap existing data-fetching functions with caching and temporary request pauses after repeated failures.

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• Building dashboard panels in vanilla TypeScript
• Saving panel sizes across page reloads
• Adding retry controls to failed data requests

Check whether a next-generation sequencing workflow has the tools, packages, reference data, and databases it needs. Generate installation and resource setup plans, record available resources, and compare them before rerunning an analysis.

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• Check installed tools before starting a sequencing workflow
• Prepare an installation plan for missing packages
• Audit reference data and database readiness

Extract a YouTube video’s full transcript and metadata, meaning details such as its title, channel, and like count, through the BrowserAct API. Use the results as source material for summaries, content research, or knowledge bases.

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• Collecting transcripts as source material for video summaries
• Gathering video text for content research
• Adding video transcripts to an internal knowledge base

Read and manipulate Flow Cytometry Standard (FCS) files. Covers loading data, accessing parameters, and basic data exploration. Use when loading and inspecting flow or mass cytometry data before preprocessing.

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Use when implementing or debugging ANY network request, API call, or data fetching. Covers fetch API, React Query, SWR, error handling, caching, offline support, loading/empty/error screen states, and Expo Router data loaders (`useLoaderData`).

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Download water level data from USGS using the dataretrieval package. Use when accessing real-time or historical streamflow data, downloading gage height or discharge measurements, or working with USGS station IDs.

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Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces. Covers FCS 2.0/3.0/3.1/3.2 internals ($PnE linear-vs-log, $DATATYPE, $SPILLOVER vs SPILL vs $COMP, $TIMESTEP), channel/parameter metadata, the silent linearize/truncate defaults, and R (flowCore, flowWorkspace, CytoML) plus Python (FlowKit, readfcs) readers. Use when loading flow or mass cytometry data, mapping detector channels to antibodies, extracting the event matrix, choosing a reader, or bridging FCS to the scanpy/AnnData ecosystem before preprocessing.

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Build local BLAST databases and run searches using NCBI BLAST+ command-line tools. Use when running >50 queries, building custom databases with -parse_seqids and -taxid, downloading prebuilt NCBI databases via update_blastdb.pl, choosing -task variants (megablast/dc-megablast/blastn/blastn-short), tuning soft/hard masking, scaling threads, or extracting hits with blastdbcmd. Encodes BLAST v5 vs v4 database format, taxonomy filtering, makeblastdb pitfalls.

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Data ingestion patterns for loading data from cloud storage, APIs, files, and streaming sources into databases. Use when importing CSV/JSON/Parquet files, pulling from S3/GCS buckets, consuming API feeds, or building ETL pipelines.

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Call APIs, load data into components, and handle the async lifecycle in Blazor. USE FOR fetching data from a backend, submitting data to an API, displaying loading/error states, registering HttpClient, building service abstractions for Auto/WebAssembly render modes. DO NOT USE for form validation (see collect-user-input), prerendering persistence (see support-prerendering), or project scaffolding (see create-blazor-project).

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Out-of-core DataFrame for billion-row data via lazy evaluation and memory-mapped files. Use when data exceeds RAM (10 GB–TB) for fast aggregation, filtering, virtual columns, and visualization without loading. Supports HDF5, Arrow, Parquet, CSV with cloud (S3, GCS, Azure). Built-in ML transformers (scaling, PCA, K-means). In-memory: polars; distributed: dask.

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Provides Next.js App Router data fetching patterns including SWR and React Query integration, parallel data fetching, Incremental Static Regeneration (ISR), revalidation strategies, and error boundaries. Use when implementing data fetching in Next.js applications, choosing between server and client fetching, setting up caching strategies, or handling loading and error states.

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You MUST use this before any data analysis or investigation - before exploring a dataset, loading or profiling data, running a model, computing a statistic, or testing an idea, and before any outcome data is touched

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Fix Flutter home feed / main screen stuck on loading spinner after login when using Riverpod StreamProvider that watches GoRouter location changes. Use when: (1) Screen shows BrandedLoadingIndicator or CircularProgressIndicator permanently after successful auth redirect, (2) Widget watches a route-type-gating provider that returns AsyncValue.loading() intermittently, (3) Logs show route location oscillating between stale and current paths during post-login transition (e.g., /welcome/* after /home/0), (4) Provider chain has double-gate: widget gates on pageContext AND data provider also gates on pageContext. Distinct from riverpod-infinite-rebuild-loop (rapid rebuilds) — this causes permanent loading state, not infinite rebuilds.

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