telnyx-whatsapp-ruby
Send WhatsApp messages, manage templates, WABAs, and phone numbers via the Telnyx WhatsApp Business API.
Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Send WhatsApp messages, manage templates, WABAs, and phone numbers via the Telnyx WhatsApp Business API.
Work with TON blockchain via the tonapi Python SDK — query accounts, transactions, jettons, NFTs, staking, DNS, emulate messages, subscribe to real-time events, and manage webhooks. Use this skill whenever the user mentions TONAPI, tonapi.io, TON blockchain data, wallet balance, jetton transfers, NFT collections, or wants to interact with TON via TONAPI. Also use when the user works with code that imports from pytonapi.rest, pytonapi.streaming, pytonapi.webhook, or pytonapi.types, or asks about TONAPI endpoints, even if they don't explicitly mention "pytonapi".
Kalshi prediction markets — events, series, markets, trades, and candlestick data. Public API, no auth required for reads. US-regulated exchange (CFTC). Covers football (EPL, UCL, La Liga), basketball, baseball, tennis, NFL, hockey event contracts. Use when: user asks about Kalshi-specific markets, event contracts, CFTC-regulated prediction markets, or candlestick/OHLC price history on sports outcomes. Don't use when: user asks about actual match results, scores, or statistics — use the sport-specific skill: football-data (soccer), nfl-data (NFL), nba-data (NBA), wnba-data (WNBA), nhl-data (NHL), mlb-data (MLB), tennis-data (tennis), golf-data (golf), cricket-data (cricket), cfb-data (college football), cbb-data (college basketball), or fastf1 (F1). Don't use for general "who will win" questions unless Kalshi is specifically mentioned — try polymarket first (broader sports coverage). Don't use for news — use sports-news instead.
Gateway to the Machina Sports premium platform — packaged agent workflows ("templates"), licensed real-time data, betting odds, and zero-latency live streams. This skill is prompt-only: it shells out to the separate `machina-cli` binary and routes the agent to a per-project Machina MCP server. Use when: the user asks for live odds, real-time telemetry, zero-latency match states, sub-second tick streams, packaged sports workflows (e.g., "Build a Bundesliga podcast bot", "Create a Polymarket arbitrage engine"), or when the open-source sports-skills are rate-limited or insufficient for the task. Don't use when: the user wants snapshot data from public APIs — use the sport-specific skill (nfl-data, polymarket, markets, …). Don't use to fetch data through raw HTTP — use the Machina MCP server, not a `requests` call.
Markets orchestration — connects ESPN live schedules with Kalshi and Polymarket prediction markets. Unified dashboards, odds comparison, entity search, and bet evaluation across platforms. Use when: user wants to see prediction market odds alongside ESPN game schedules, compare odds across platforms, search for a team/player on Kalshi or Polymarket, check for arbitrage between ESPN odds and prediction markets, or evaluate a specific game's market value. Don't use when: user wants raw prediction market data without ESPN context — use polymarket or kalshi directly. For pure odds math (conversion, de-vigging, Kelly) — use betting. For live scores without market data — use the sport-specific skill.
Install or use the ccap CLI for camera capture, webcam inspection, device listing, frame capture, and video metadata. Use when you need to work with CameraCapture on macOS, Linux, or Windows, especially for listing devices, checking device capabilities, capturing frames, inspecting video files, or choosing between existing install, Homebrew, source build, and release-binary fallback.
Writing render settings to control rendering behavior. Use when user asks to change render settings, set max bounces, configure path tracing, change render quality, or modify RTX settings on a RenderProduct.
Download pre-exported models from Qualcomm AI Hub and run inference on-device. Supports QNN_CONTEXT_BINARY, QNN_DLC, VOICE_AI, ONNX, TFLITE formats. All on-device (NPU/HTP) inference runs through qai_appbuilder (QNNContext), loading the QNN context binary (.bin) or .dlc. Standard onnxruntime is used only for an optional CPU baseline comparison.
Use this skill when a developer asks how to begin using Aspire — installing the Aspire CLI, creating a new Aspire app, running it locally, or finding the authoritative docs, integration catalog, or API reference on aspire.dev. Use it for questions like "how do I install aspire?", "how do I create a new aspire app?", "how do I run my aspire app?", or "where is the documentation for aspire?". Do not use it for operating an existing Aspire AppHost (use the official `aspire` skill at github.com/microsoft/aspire/tree/main/.agents/skills/aspire), authoring AppHost code, or adding integrations to an existing app.