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Found 2,040 Skills
Turso (Limbo) database helper — an in-process SQLite-compatible database written in Rust. Formerly known as libSQL / libsql. Replaces @libsql/client, libsql-experimental for Turso use cases. Works in Node.js, browser (WASM + OPFS for persistent local storage), React Native, and server-side. Features: vector search, full-text search, CDC, MVCC, encryption, remote sync. SDKs: JavaScript (@tursodatabase/database), Browser/WASM (@tursodatabase/database-wasm), React Native (@tursodatabase/sync-react-native), Rust (turso), Python (pyturso), Go (tursogo). This skill contains all SDK documentation needed to use Turso — do NOT search the web for Turso/libsql docs.
Perform language and framework specific security best-practice reviews and suggest improvements. Trigger only when the user explicitly requests security best practices guidance, a security review/report, or secure-by-default coding help. Trigger only for supported languages (python, javascript/typescript, go). Do not trigger for general code review, debugging, or non-security tasks.
Create reports in Frappe including Report Builder, Query Reports (SQL), and Script Reports (Python + JS). Use when building data analysis views, dashboards, or custom reporting features.
Interactive tutorial that guides engineers through building their own coding agent (agentic loop) from scratch using raw HTTP calls to an LLM API. Supports Gemini, OpenAI (and compatible endpoints), and Anthropic. Supports TypeScript, Python, Go, and Ruby. Detects progress automatically. Use when someone says "build an agent", "teach me agents", or "/build-agent".
Integrate Perplexity API for web-grounded AI responses and search. Covers Sonar models, Search API, SDK usage (Python/TypeScript), streaming, structured outputs, filters, media attachments, Pro Search, and prompting. Keywords: Perplexity, Sonar, sonar-pro, sonar-reasoning-pro, sonar-deep-research, web search API, grounded LLM, chat completions, perplexityai SDK, image attachments, PDF analysis.
Creates pytest fixtures following project patterns including factory fixtures, async fixtures, and multi-layer organization. Use when setting up test fixtures, creating test data, organizing test utilities, or structuring conftest.py files. Works with Python test files, pytest configuration, and .py test utilities.
Provides 3-tier validation approach for Home Assistant dashboards including pre-publish validation (entity checks, config structure), post-publish verification (log analysis), and visual validation (browser console, rendering). Use when validating HA dashboards, checking dashboard configs, verifying entity IDs, debugging rendering issues, or before deploying dashboard changes. Triggers on "validate dashboard", "check HA config", "dashboard errors", "entity not found", or "test dashboard". Works with Home Assistant WebSocket/REST APIs, Chrome extension MCP tools, Python dashboard builders, and YAML dashboard configurations.
Code review and PR review skill for Python PySide6/Qt 6.8+ applications. Focuses on modern best practices, performance, thread safety, signal/slot patterns, Model/View architecture, QML integration, and async patterns. Use when reviewing Python Qt code, PySide6 PRs, GUI application code, or when asked to review code that uses QtWidgets, QtQuick, QtCore, QtGui, or any Qt module. Catches common anti-patterns, memory issues, thread violations, and suggests modern Qt 6.8+ idioms.
Use OpenSearch vector search edition via the Python SDK (ha3engine) to push documents and run HA/SQL searches. Ideal for RAG and vector retrieval pipelines in Claude Code/Codex.
Process images for web development — resize, crop, trim whitespace, convert formats (PNG/WebP/JPG), optimise file size, generate thumbnails, create OG card images. Uses Pillow (Python) — no ImageMagick needed. Trigger with 'resize image', 'convert to webp', 'trim logo', 'optimise images', 'make thumbnail', 'create OG image', 'crop whitespace', 'process image', or 'image too large'.
Use this skill when spreadsheet files are the primary input or output. This means the user wants to: open, read, edit, or repair existing .xlsx, .xlsm, .csv, or .tsv files (e.g., add columns, calculate formulas, format, create charts, clean messy data); create new spreadsheets from scratch or from other data sources; or convert between spreadsheet file formats. Trigger this especially when the user references a spreadsheet file by name or path—even casually (such as "the xlsx in my downloads")—and wants to process it or generate content from it. It's also used to clean or reorganize messy tabular data files (rows with incorrect formatting, misaligned headers, garbage data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do not trigger this when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
Test, commit, and push in one atomic workflow. Runs Go and Python tests, commits with conventional message, pushes to current branch.