Total 52,636 skills, Data Processing has 2638 skills
Showing 12 of 2638 skills
Start-here router and tradecraft baseline for any OSINT investigation. Sets authorized scope, turns a vague request into an answerable intelligence question, writes a collection plan, picks the right workflow skill for the starting selector, and applies source grading and competing-hypothesis discipline. Use for "investigate this person/company/domain", "do OSINT on X", "where do I start", or any open-source intelligence, due diligence, or attribution task.
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
Surfaces social-layer signals for crypto markets. Three capability groups: news (latest aggregated crypto news feed, filter articles by coin symbol, run full-text keyword searches, fetch a single article in full, and list available upstream platforms — blockbeats, odaily, theblock and similar — for use as filters); sentiment (rank coins by social mention volume over 1h / 4h / 24h, plus per-coin bullish/bearish/neutral counts with an optional time-bucketed trend); vibe (per-contract hotness score over 24h / 72h / 7d / 30d with timeline and sample KOLs per bucket, plus a TOP50 KOL leaderboard sortable by engagement, mentions, or impressions). Triggers: 'latest crypto news', 'BTC headlines', 'search news for X', 'is BTC bullish', 'hottest coins by chatter', 'who is tweeting about <token>', 'vibe score', 'first-mention KOL', and Chinese variants like '最新加密新闻', '搜索新闻', '市场情绪', '情绪排行', 'KOL榜', '热度走势'. Also handles x402/402 payment, quota, MARKET_API_*_OVER_QUOTA, and confirming:true notifications on social endpoints.
Universal scraper for any OpenWeb Ninja API. Scrape jobs, business listings, products, reviews, news, social profiles, finance data, and more. Use for lead generation, market research, competitor analysis, content monitoring, price tracking, or any structured data extraction task.
Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review writing use peer-review.
Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and specific journal formatting (Nature, Science, Cell). Orchestrates matplotlib/seaborn/plotly with publication styles. For quick exploration use seaborn or plotly directly.
Integrate Firecrawl `/crawl` into product code for bulk extraction across a site or site section. Use when a feature needs many related pages, such as documentation sets, help centers, or blogs, and page-by-page `/scrape` would be too manual.
Guided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test selection guidance. For implementing specific models programmatically use statsmodels.
Interactive visualization library. Use when you need hover info, zoom, pan, or web-embeddable charts. Best for dashboards, exploratory analysis, and presentations. For static publication figures use matplotlib or scientific-visualization.
Low-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots use seaborn; for interactive plots use plotly; for publication-ready multi-panel figures with journal styling, use scientific-visualization.
Spreadsheet toolkit (.xlsx/.csv). Create/edit with formulas/formatting, analyze data, visualization, recalculate formulas, for spreadsheet processing and analysis.
Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization.