AI Chat Assistant
Chat with Toolvore AI — ask anything, brainstorm, or get help.
This tool sends the text you enter to an AI provider to generate a response. Don't paste secrets or personal data. No files are uploaded.
Ask a question in ordinary language and this chat tool streams an answer back as it is written, keeping the earlier turns on screen so each follow-up builds on what was already said instead of starting a fresh conversation.
How to use it
- 1Type into the box at the bottom, or click one of the four starter suggestions to send it straight away.
- 2Press Enter to send; Shift+Enter adds a line break instead of sending.
- 3Press Stop to cut a long reply short, then ask a follow-up — the thread stays in view.
Example
- Input
- Explain quantum computing in simple terms
- Output
- A few short Markdown paragraphs of plain-English explanation, appearing progressively as the model writes them.
The wording differs on every run — a language model does not return one fixed answer for a given question.
What happens to your data
Each turn sends the whole thread, not just your latest line: the messages are held in one React state array and that entire array is posted to /api/ai, which forwards it to Anthropic's API to be answered — so something mentioned in your first message is transmitted again with your tenth. Our route stores nothing and a page reload empties the conversation, but the text has still left your device for someone else's infrastructure, so keep passwords, API keys and other people's personal details out of it. Replies are generated prose, confident whether or not they are right, and anything you plan to act on needs checking elsewhere.
Last updated August 2026
Most people arrive at a chat box in the middle of something else — a half-remembered term, an error message that means nothing, a paragraph that has to be rewritten before a meeting. The appeal is not having to know the name of the thing you need — you describe the problem in ordinary words and something works out what you meant.
The decision worth making before you type is whether you want a fact or a piece of work. A language model is dependable at the second — restructure this, explain this more simply, give me three ways to say it — because you can read the result and judge it yourself. It is much less dependable at the first, where a wrong answer looks exactly like a right one. Questions with a single checkable answer are the ones to treat sceptically, not the vague ones.
The assistant here also carries the site's own tool catalogue, generated from the same registry the pages are built from, so it can name the tool that handles a given job and link to it rather than inventing a plausible address. Outside that catalogue it is a general-purpose model with a general-purpose model's blind spots.
The common mistake is loading one message with six unrelated questions, then finding each answered shallowly. A short question followed by a correction gets further than a long brief that has to be right first time.
How it works
Toolvore sends your messages to a route on the site, which attaches a system prompt listing every tool, category and workflow available here, generated at build time from the registry rather than typed by hand, then passes the result to Anthropic to be answered, by Claude Sonnet 5 unless an environment variable names a different model. The reply comes back as a stream of plain text, rendered as it arrives through a Markdown parser and a sanitiser, so headings, lists and code blocks appear formatted while anything that would inject markup is stripped. The weak points are structural. There is no file upload and no browsing step, so the model sees the text of your messages and nothing else: a pasted link gives it an address, not a page. Its knowledge outside this catalogue is whatever it was trained on, with no live source behind it, and the reply length is capped, so a large request is truncated rather than continued.
Common use cases
- Working out which tool handles a job you can only describe in words
- Getting a plain-English explanation of a term before a meeting
- Checking what a phrase in a contract or an error message actually means
- Asking follow-ups until an explanation lands at the right level
- Turning rough notes into something you can read back later
- Drafting a first version of an email you are stuck on
Frequently asked questions
Is an AI chatbot better than a search engine?＋
It depends on whether you can name what you need. A search engine matches words, so it works once you know the term and want a source you can check. A chatbot works from a description, which is why it wins on questions shaped like what is the thing that does X, and on rephrasing or summarising. Where it loses is provenance: a search result comes with an author and a date, a chat reply with neither. For anything you will rely on, ask the chatbot for the vocabulary, then search with it.
Why do AI chatbots make things up?＋
Because they are built to produce plausible text rather than to look anything up. The model predicts what should come next given everything before it, and a confident invention scores as well on that measure as a correct answer — there is no separate step where it checks. Fabrications therefore cluster around specifics: citations, statistics, version numbers, dates, names. The wording carries no signal either — it sounds equally sure both ways. Treat anything that could be looked up as something to look up, and reserve trust for work you can verify by reading it.
Does a chatbot remember earlier messages, and what happens in a long conversation?＋
It remembers only what is put in front of it. Within one thread there is a ceiling: the route forwards up to sixty thousand characters of conversation and drops the oldest turns to stay under it, always leaving a user message at the front. So in a long session the earliest exchanges quietly fall out of range while still sitting on your screen, which is how an assistant appears to forget a constraint you set at the start. When the subject changes, the New conversation button clears the thread rather than letting stale context steer the next answer.
What should you never type into an AI chatbot?＋
Anything you would not send to a company you have no contract with. Passwords, API keys and access tokens are the obvious ones. Less obvious are other people's details: a customer's address in a complaint you are drafting, a colleague's reason for absence, an unannounced product name. The site's own route keeps nothing, but keeping nothing is not the same as never having it — the text still crosses the network to a model provider to be answered. Redact before you paste, and describe a sensitive document rather than paste it.
Why did the answer stop in the middle of a sentence?＋
Because replies have a length ceiling, and reaching it ends the response wherever it happens to be. The cap here is four thousand tokens of output, and when it is hit a bracketed note is appended saying so, which is what separates a truncated answer from a finished one. Asking again identically will produce the same stop. Ask for the remainder instead, or narrow the request — the second half only, or the list without the explanations. A reply that ends abruptly with no bracketed note usually means the connection dropped rather than the limit.
How do you write a prompt that gets a better answer?＋
Give it the context you are carrying in your head: who the answer is for, what you already know, what you will do with it, and what a bad answer would look like. Those four do more than any phrasing trick. Ask for a shape as well as a subject — three options, one line each, returns something usable where tell me about X returns an essay. And correct rather than restart. A reply that is close but too technical needs one follow-up saying so, with the earlier turns still there to build on.
Can a chatbot read a file, open a link, or look something up online?＋
Not this one. It receives the text of your messages and nothing else, so pasting a URL hands it the address rather than the page, and any account of what is at that address is guesswork. The same applies to anything recent: with no live source, current prices, today's news and last week's release notes sit outside what it can honestly answer. For work on an actual file, the browser-based tools elsewhere on the site process it on your own machine — a different mechanism entirely.
Why does it say the AI is switched off, or ask me to wait?＋
Two separate things produce that. The page asks the server on load whether an API key is configured; if none is, the box is disabled before you write a question rather than after — every non-AI tool on the site still works in that state. The other is rate limiting: six requests a minute per address, and going past it returns a message asking you to wait a few seconds. Both are deliberate. An AI endpoint with no ceiling is an open tab on somebody's card, and a limit that stops a runaway script costs a person typing nothing.
