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Found 286 Skills
Guide for using Nushell for structured data pipelines and scripting. Use when writing shell scripts, processing structured data, or working with cross-platform automation.
This skill should be used when building data processing pipelines with CocoIndex v1, a Python library for incremental data transformation. Use when the task involves processing files/data into databases, creating vector embeddings, building knowledge graphs, ETL workflows, or any data pipeline requiring automatic change detection and incremental updates. CocoIndex v1 is Python-native (supports any Python types), has no DSL, and is currently under pre-release (version 1.0.0a1 or later).
Coin comprehensive analysis. Use this skill whenever the user asks to analyze a single coin. Trigger phrases include: analyze, how is, worth buying, look at. MCP tools: info_coin_get_coin_info, info_marketsnapshot_get_market_snapshot, info_markettrend_get_technical_analysis, news_feed_search_news, news_feed_get_social_sentiment.
Synthesize customer feedback into thematic clusters when the user asks to analyze feedback, review VoC data, or understand customer sentiment
Analyze Apple Health export ZIP. Run local prepare to generate structured insights, then produce a professional health report based on cross-metric analysis and historical context.
Install or update DuckDB extensions. Each argument is either a plain extension name (installs from core) or name@repo (e.g. magic@community). Pass --update to update extensions instead of installing.
Transform, filter, reshape, join, and manipulate football data. Use when the user needs to clean data, merge datasets, convert between formats, handle missing values, work with large datasets, or do any data manipulation task on football data.
Football data analytics — the single entry point. Use whenever the user mentions football data, xG, expected goals, match analysis, player stats, scouting, match reports, shot maps, passing networks, Premier League data, Champions League stats, scraping FBref/Understat/Transfermarkt, building football charts, or anything football analytics related. Routes to specialised sub-skills automatically. Also handles first-time setup and profile management.
Research Xiaohongshu accounts from validated recent-post surfaces, then aggregate account-level content signals without pretending follower or bio metrics are available when the validated profile actor is empty.
Find substitute materials using CWICR data. Identify equivalent alternatives based on function, cost, and availability.
Read, write, and manipulate SEG-Y seismic data files. Fast C library with Python bindings for trace, header, inline, and crossline access. Use when Claude needs to: (1) Read/inspect SEG-Y files, (2) Extract trace data or headers, (3) Access 3D survey data by inline/crossline, (4) Create new SEG-Y files from arrays, (5) Modify existing SEG-Y files, (6) Extract subsets of seismic data, (7) Read/write Seismic Unix format.
Gravity and magnetic data processing and forward modelling using Fatiando a Terra. Use when Claude needs to: (1) Compute gravity forward models (point masses, prisms, tesseroids), (2) Apply terrain/Bouguer corrections, (3) Grid scattered potential field data with equivalent sources, (4) Perform upward/downward continuation, (5) Calculate magnetic anomalies from magnetized bodies, (6) Apply derivative filters (gradients, tilt angle), (7) Process regional or local gravity surveys.