Total 54,172 skills, Data Processing has 2771 skills
Showing 12 of 2771 skills
Convert RVT/RFA files to Excel databases. Extract BIM element data, properties, and quantities.
GSLIB-inspired geostatistics library for variogram analysis, kriging, and simulation. Use when Claude needs to: (1) Calculate experimental variograms, (2) Fit variogram models, (3) Perform simple/ordinary kriging, (4) Run sequential Gaussian simulation (SGSIM), (5) Apply normal score transforms, (6) Decluster spatial data, (7) Generate multiple realizations for uncertainty.
Every SEC filing, every XBRL fact, every insider trade — synced into a local SQLite store you can pivot, search, and watch offline. Trigger phrases: `look up an SEC filing`, `check insider trading on`, `compare quarterly financials for`, `watch SEC filings for`, `use sec-edgar`.
Reads AR/AP, historical cash timing, and known fixed costs from QuickBooks, PayPal, Stripe, or Square — or a CSV upload — and produces a 30/60/90-day cash flow forecast with percentage-variance confidence bands and named risk flags. Delivers a chat summary and a downloadable XLSX. Use when the user asks "forecast my cash flow," "will I make payroll," mentions "runway," or says "cash crunch." Falls back to CSV upload when no connector is live.
Diagnose why a product metric changed (dropped, spiked, or plateaued) by orchestrating breakdowns, actors, paths, lifecycle, retention, and annotations queries. Use when the user reports an anomaly, asks "why did X change?", or needs root-cause analysis for a trend, funnel, retention, stickiness, or lifecycle metric.
Analyze stocks and cryptocurrencies using Yahoo Finance data. Supports portfolio management, watchlists with alerts, dividend analysis, 8-dimension stock scoring, viral trend detection (Hot Scanner), and rumor/early signal detection. Use for stock analysis, portfolio tracking, earnings reactions, crypto monitoring, trending stocks, or finding rumors before they hit mainstream.
Searches for homologous protein sequences using MMseqs2 (fast, default) or BLAST (comprehensive, fallback). Trigger this whenever the user provides a protein sequence or FASTA file and asks to find homologues, sequence matches, or wants to infer protein function based on sequence similarity, but not when the user wants to infer protein function based on structural similarity.
Retrieve protein and nucleotide sequences from NCBI databases using E-utilities. Supports direct accession lookup, CDS translation, gene+organism search, locus lookup, PubMed-linked sequences, patent protein extraction, and organism+length fallback search. Use when you need to fetch biological sequences by accession, gene name, locus tag, PubMed ID, or patent number.
Connect SaaS data (HubSpot, Stripe, Salesforce, GitHub, Slack, etc.) to Wren Engine for SQL analysis. Guides the user through the full flow: install dlt, pick a SaaS source, set up credentials, run the data pipeline into DuckDB, then auto-generate a Wren semantic project from the loaded data. Use this skill whenever the user mentions: connecting SaaS data, importing data from an API, dlt pipelines, loading HubSpot/Stripe/Salesforce/GitHub/Slack data, querying SaaS data with SQL, or setting up a new data source from a REST API. Also trigger when the user already has a dlt-produced DuckDB file and wants to create a Wren project from it.
Guides hands-on actuarial analyst work for insurance, reinsurance, and pension—reserving and loss development (IBNR, triangles, chain-ladder diagnostics), pricing and rate indication support (experience, trend, credibility, basic GLM at spec level), data validation and model I/O review, reporting packs and workpapers, assumption application under actuary direction, and statutory tie-outs at analyst depth. Use when the user mentions actuarial analyst, loss development, IBNR, reserve analysis, rate indication, pricing support, actuarial workpaper, triangle analysis, credibility, experience study, actuarial reporting, or reserve roll-forward—not actuary sign-off (actuary), consulting engagements (actuarial-consulting), assumption governance (assumption-setting), ALM strategy (asset-liability-management), P&C legal depth (property-casualty-insurance), charts only (data-visualization), or ETL-only pipelines (data-scrubbing).
Guides advanced short-term actuarial mathematics aligned with SOA ASTAM and P&C/health-adjacent modeling—severity and frequency distributions, aggregate and compound loss models, Bühlmann and Bühlmann-Straub credibility, ratemaking and experience rating, short-term reserving at the math level, MLE and goodness-of-fit, and risk measures (VaR, TVaR). Tool-agnostic and concept-first. Use when the user mentions advanced short-term actuarial mathematics, ASTAM, severity model, frequency model, aggregate loss, compound distribution, Bühlmann credibility, experience rating, ratemaking, pure premium, negative binomial frequency, tail factor, TVaR, or short-term actuarial models—not life contingencies (life-health-insurance), Excel workpapers only (actuarial-analyst), appointed actuary sign-off (actuary, appointed-chief-actuary), assumption governance (assumption-setting), P&C legal/operations depth (property-casualty-insurance), or general ML (data-scientist, quantitative-researcher).
Use when writing Python that processes biological sequences (DNA/RNA/protein) with the seqpro package — encoding, one-hot, k-mer shuffling, reverse complement, GC content, variable-length sequence batches, or anything involving seqpro's `Ragged` array. Covers the seqpro API surface and the conventions you need to use it correctly.