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Found 43 Skills
Mine Gmail history into a local flat-file knowledge base (~/.cortex/). Use when asked to "run the cortex", "mine emails", "cortex run", "cortex dry run", "set up the cortex", "cortex from DATE", or "mine my inbox". Extracts contacts, clients, communications and knowledge facts into portable JSONL/JSON files. Requires gws CLI and ANTHROPIC_API_KEY.
Fetch recent posts from one or more X/Twitter accounts through twitterapi.io, output structured JSON/CSV records, optionally sync records to Feishu/Lark Bitable through feishu-cli, and optionally guide recurring execution through OpenClaw, Codex automations, cron, or launchd. Use when the user wants to monitor X bloggers, collect recent tweets, export tweet metrics, append tweets to Feishu Bitable, or set up a scheduled Twitter/X account tracking workflow.
Interact with Excel files (.xlsx, .xlsm, .xlsb, .xls, .ods) using the agent-xlsx CLI for data extraction, analysis, writing, formatting, visual capture, VBA analysis, and sheet management. Use when the user asks to: (1) Read, analyse, or search data in spreadsheets, (2) Write values or formulas to cells, (3) Inspect formatting, formulas, charts, or metadata, (4) Take screenshots or visual captures of sheets, (5) Export sheets to CSV/JSON/Markdown, (6) Manage sheets (create, rename, delete, copy, hide), (7) Analyse or execute VBA macros, (8) List/export embedded objects (charts, shapes, pictures), (9) Check for formula errors, or (10) Any task involving Excel file interaction. Prefer over openpyxl/pandas scripts — faster, structured JSON optimised for AI.
Download workflow run results, export segment data, and monitor run metrics using the Cargo CLI. Use when the user wants run metrics, error rates, data export, or download results for their Cargo workspace. For billing and credit usage, use the cargo-billing skill instead.
Create, visualize, and analyze lithological and stratigraphic logs for well data. Use when Claude needs to: (1) Create lithology columns from depth intervals, (2) Parse geological descriptions into structured logs, (3) Visualize stratigraphic columns with patterns and colors, (4) Perform well-to-well correlations, (5) Extract statistics like net-to-gross ratios, (6) Define rock type lexicons and legends, (7) Export lithology data to CSV/LAS/JSON.
Murder Mystery 2 inventory tracking, analytics dashboard, and gameplay optimization toolkit for Roblox
Reference for App Store Connect crash analysis, TestFlight feedback, metrics dashboards, and data export workflows
Fetch, organize, and analyze LangSmith traces for debugging and evaluation. Use when you need to: query traces/runs by project, metadata, status, or time window; download traces to JSON; organize outcomes into passed/failed/error buckets; analyze token/message/tool-call patterns; compare passed vs failed behavior; or investigate benchmark and production failures.
High-performance data analysis using Polars - load, transform, aggregate, visualize and export tabular data. Use for CSV/JSON/Parquet processing, statistical analysis, time series, and creating charts.
Implements Syncfusion React Grid component for feature-rich data tables and grids. Use this when working with data display, sorting, filtering, grouping, aggregates, editing, or exporting. This skill covers grid configuration, CRUD operations, virtual scrolling or infinite scrolling, hierarchy grids, state persistence, and advanced data management features for data-intensive applications.
Implements and customize Syncfusion .NET MAUI DataGrid (SfDataGrid) for displaying tabular data. Use when working with MAUI data grids, SfDataGrid, tabular data display, data binding to grids, or column configuration. Covers editing cells, sorting, filtering, grouping, paging, exporting to Excel/PDF, row operations, selection, and summaries.
Execute read-only T-SQL queries against Fabric Data Warehouse, Lakehouse SQL Endpoints, and Mirrored Databases via CLI. Default skill for any lakehouse data query (row counts, SELECT, filtering, aggregation) unless the user explicitly requests PySpark or Spark DataFrames. Use when the user wants to: (1) query warehouse/lakehouse data, (2) count rows or explore lakehouse tables, (3) discover schemas/columns, (4) generate T-SQL scripts, (5) monitor SQL performance, (6) export results to CSV/JSON. Triggers: "warehouse", "SQL query", "T-SQL", "query warehouse", "show warehouse tables", "show lakehouse tables", "query lakehouse", "lakehouse table", "how many rows", "count rows", "SQL endpoint", "describe warehouse schema", "generate T-SQL script", "warehouse performance", "export SQL data", "connect to warehouse", "lakehouse data", "explore lakehouse".