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Found 1,115 Skills
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.
Generate draw.io diagrams as .drawio files, optionally export to PNG/SVG/PDF with embedded XML
Run the TikSpyder tool to collect TikTok data — search by keyword, username, or hashtag, download videos, extract keyframes, and export structured data. Use this skill whenever the user wants to collect TikTok data, search TikTok profiles or hashtags, search TikTok videos, download TikTok content, run tikspyder, or launch the TikSpyder Streamlit interface. Also trigger when the user mentions data collection from TikTok, even if they don't say "tikspyder" by name.
Specification-first AI development powered by Ouroboros. Socratic questioning exposes hidden assumptions before writing code. Evolutionary loop (Interview → Seed → Execute → Evaluate → Evolve) runs until ontology converges. Ralph mode persists until verification passes — the boulder never stops. Use when user says "ralph", "ooo", "don't stop", "must complete", "until it works", "keep going", "interview me", or "stop prompting".
Code generation utilities for json-render. Use when generating code from UI specs, building custom code exporters, traversing specs, or serializing props for @json-render/codegen.
Import/export pipeline for UnoPim. Activates when configuring imports, exports, debugging job pipelines, or creating data transfer profiles; or when the user mentions import, export, CSV, Excel, job, queue, batch, or data transfer.
Answer questions about Module Federation (MF) — configuration, runtime API, build plugins (Webpack/Rspack/Rsbuild/Vite), framework integration (React/Vue/Next.js/Modern.js/Angular), shared dependencies, exposes, remotes, debugging, troubleshooting, and micro-frontend architecture. Use this skill when the user asks anything about module federation, remote modules, shared deps, mf-manifest, federation runtime, or micro-frontends with MF.
Run and monitor existing (B2C/demandware/SFCC) jobs using the b2c cli, import/export site archives (IMPEX). Always reference when using the CLI to run jobs, import or export site archives, check job execution status, or trigger search indexing. For creating new jobs, use b2c-custom-job-steps skill instead.
Generates importable n8n workflow JSON files that sync data between Personize and 400+ apps. Produces ready-to-import workflows for batch sync, webhook ingestion, per-record AI enrichment, and data export — no code required. Use this skill whenever the user wants no-code integrations, visual workflows, n8n automation, or to connect Personize to HubSpot, Salesforce, Google Sheets, Slack, Postgres, or any app without writing code. Also trigger when they mention 'workflow automation', 'scheduled sync without code', 'visual pipeline', or 'connect Personize to [app]' and don't want to write TypeScript.
Feishu Document Assistant. Read and write Feishu cloud documents and knowledge bases, supporting creation, export, precise editing, synchronization to knowledge bases, and group message notifications. Use this Skill when users mention Feishu documents, knowledge bases, wiki, or send feishu.cn links.
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".
Use when migrating to another AI platform — exports all stored memories, context, preferences, and instructions so you can import them elsewhere