HubVibe

Base wallet lookup / address balance: ETH balance, transaction count (nonce) and whether the address is a smart contract or an ordinary wallet (EOA), live from Base mainnet in one call. Use it to check a counterparty, deposit address or contract before paying it. Input: address (0x...). For token balances or any other read use chain.rpc.

Page speed and page weight audit of a web page from one real browser load: total bytes transferred, HTTP request count and DOM node count, measured rather than estimated, with findings when the page is heavy. Page-weight signals, not Core Web Vitals.

Web search with an answer: real-time search of Brave's independent web index, answered from the current results only, with every source URL and title returned, never the model's memory. Use it when an agent needs up-to-date information, latest news, prices or facts from the web. Input: query; optional language. Raw result list (SERP): search.results. Sources read in full with citations: research.web.

Web scraping / web page to clean text: any URL rendered in a real browser (JavaScript pages included) and returned as readable text with title, description and links. Use it to read an article, docs page or product page before summarising or extracting. Input: url. Raw status, headers and body: fetch.raw. A question answered from the page: research.brief.

Summarize and analyze a web page: the URL is rendered in a real browser, its content extracted, and a written brief answering your question returned, grounded in that page only and saying so when the page does not answer. Use it for competitor pages, docs, articles and listings. Input: url; optional question. Fixed JSON fields: research.page_facts. Needs a web search: research.web.

LLM text generation / chat completion: a raw completion from your prompt with optional system message, max_tokens and temperature; Gemini by default, other configured models by provider and model. Use it for drafting, rewriting, translation, classification or any prompt, paid per call with no API key or account. Input: prompt. Answer grounded in your own text: llm.analyze.

One prediction market by slug: a Polymarket market's question and the current probability of each outcome as a percentage. Use it to track a market you already know. Input: slug. Search markets by topic: market.prediction.

HTTP fetch / GET any URL: exactly what the server sent, status code, headers and body, plus the final URL after redirects. Every status is a result, so a 404 or 500 from the target is delivered, not failed. Use it for API checks, uptime probes and raw HTML. Input: url. Readable text from a rendered page: extract.page.

Question answering over your own text: ask a question about material you supply and get an answer grounded only in that text (Gemini). If the text does not contain the answer it says so instead of guessing. Use it for summaries, Q&A and checks over documents, emails and pages. Input: text, question; optional language. Fixed JSON fields: llm.extract.

Ask a database in plain English (text to SQL): any BigQuery table, including Google's public datasets. The SQL is written for you, run under a byte ceiling, and the rows are read back into a written answer, returned with the SQL, columns and rows it used. Use it for analytics questions without writing SQL. Input: question, table; optional columns.

Website change detection, step two: re-fetch a page saved with monitor.snapshot and get whether it changed, how old the baseline is, and a written summary of what changed. Use it to track price changes, terms updates, new job posts or competitor moves. Input: url; optional language.

AI image generation / text to image: one image from a text prompt with Google Imagen 4, returned as base64 image bytes with its MIME type. Use it for illustrations, thumbnails, product mockups and social images. Input: prompt; optional aspect_ratio.

Run Python code in a sandbox: execute Python in Google's hosted sandbox (not on this service's machines) and get the code, its printed output and the outcome back. Use it for calculations, data transforms and checks an agent should not do in its head. Input: code. Questions over BigQuery data: data.query.

Directions between two places: route and travel time by car, walking, bicycle or transit through Google Maps Grounding Lite. Use it for trip planning and ETAs. Input: origin, destination; optional travel_mode (DRIVE, WALK, BICYCLE, TRANSIT; default DRIVE).

Places near me / local search anywhere: 'coffee near the Ferry Building, San Francisco', 'ramen near Shibuya Station', 'pharmacy' at coordinates. From Overture Maps open places data (80M+ places): name, category, distance, address, website, phone, brand, open status and confidence, nearest first; the area widens when nothing is close. Input: query; optional near, lat and lng, radius_m, limit.

Text to speech (TTS): convert text to natural spoken MP3 audio with Google Cloud Text-to-Speech, returned as base64. Use it for voice replies, narration, audio versions of text and accessibility. Input: text; optional voice name.

AI video generation / text to video: a short clip from a text prompt with Google Veo, returned as base64 video bytes (or a GCS URI when large) with its MIME type, optionally with generated audio. Input: prompt; optional aspect_ratio (16:9 or 9:16), duration_seconds (4, 6 or 8), generate_audio.

Company research report: what a company does, its products and anything notable, from the live web (official site and Wikipedia first) and recent GDELT news, every claim cited to a numbered source, thin or conflicting evidence disclosed. Use it for due diligence, sales prep and competitor research. Input: company name; optional max_sources. Structured firmographics in one cheap call: company.enrich.

Fact check claims against sources: up to 10 claims checked against up to 4 source URLs you name; each comes back SUPPORTED, CONTRADICTED or UNSUPPORTED with the exact quote the verdict rests on. Use it to verify AI output, citations or statements before publishing. Input: claims[], sources[]. A question but no sources yet: research.web.

Anomaly detection on a time series: score recent periods against history with BigQuery AI.DETECT_ANOMALIES (TimesFM). Give one table and its latest periods are scored against its own history, or a history and a target table. Returns every checked row with bounds, anomaly flag and probability, plus the anomaly count. Input: history_table, target_table, timestamp_col, data_col; optional target_last, threshold, id_cols.

Time-series forecasting: forecast any BigQuery table with Google's pretrained TimesFM model (AI.FORECAST), nothing to train. Point it at the table, timestamp column and value column and get forecast rows with bounds for the horizon you set, per series with id_cols. Use it for sales, traffic, demand or metric forecasts. Input: table, timestamp_col, data_col; optional horizon, id_cols.

Structured facts from a web page / scrape to JSON: name the fields you need (pricing, plans, contact, product names, anything) and get exactly those keys back as JSON from the live page rendered in a real browser, null where the page does not say. Use it for price monitoring, lead data and catalog extraction. Input: url, fields[].

Weather forecast anywhere on Earth: current conditions, the next 24 hours and a seven-day forecast (temperature, precipitation, wind, humidity, cloud, pressure, condition) from MET Norway's forecast model, plus active US National Weather Service alerts for US locations. Input: location as a place name, US street address or airport code, or lat and lng.

Speech to text / audio transcription: transcribe up to 60 seconds or 10 MB of audio with Google Cloud Speech-to-Text and get the transcript with its confidence and detected language. Use it for voice notes, call snippets and clips. Input: audio_base64; optional language_code. Longer audio is refused before payment.

Trading and portfolio math: returns and CAGR, volatility, Sharpe and Sortino, max drawdown, VaR/CVaR, beta, alpha and correlation vs a benchmark, SMA/EMA, RSI, Bollinger bands, Black-Scholes option price with Greeks, and the Kelly fraction, over prices you send or a ticker fetched live. Deterministic, every formula named, no LLM. Input: prices or symbol; optional metrics, benchmark, option, kelly.

Product availability and price check: is it in stock and buyable right now, at what price, in which options (sizes, colours, dates, rooms), which option matches the variant you name, quantity and ship-to eligibility where the page states them, with evidence and a checked_at stamp. Reads any product or booking page (schema.org, Open Graph, Shopify JSON; a browser only when needed). Input: url; optional variant, quantity, ship_to.

Predictive probability and regression engine: least-squares linear regression with standard errors, confidence and prediction intervals, a fitted normal distribution with quantiles and probability queries (P(y > t)), exact Student t and Jarque-Bera p-values. Points inline or from a BigQuery table. Deterministic arithmetic, no LLM: the same input always returns the same numbers. Input: points or table with x_column, y_column; optional metrics, predict_x, probability_queries.

Travel time with live traffic between two places, from the Google Routes API at call time: duration with traffic, duration without, the delay, distance, route description, warnings and advisories. Places as addresses, names or 'lat,lng'. Use it for ETAs, delivery windows and trip planning. Input: origin, destination; optional travel_mode, departure_time, traffic.

HubVibe Agent (quick): hand it any task in plain words and get the finished result in one call. Research a company or a person of interest, check a website, screen a name, read the markets, compare options, pull the facts: you get a headline, the key points, the full answer, its sources and every tool step. Up to 4 steps. Charged only when the answer is delivered. Input: task; optional context, fields for a JSON answer, language.

Dataset file to JSON rows: a CSV, TSV, XLSX or JSON link from any portal, an e-Stat (Japan) download or a data.go.kr (Korea) dataset page. Encoding detected (Korean, Japanese, Chinese, UTF and Western code pages), header row found, numbers typed, XLSX sheets selectable, large files capped and disclosed. Use it after opendata.search or on any data file URL. Input: url; optional max_rows, sheet, encoding, delimiter.