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Docs/How Keplar works

Small talk and simple questions

Why "hi" and "thanks" cost nothing, how Keplar detects casual chat, and what happens to short factual questions.

Updated October 3, 20261 min read

On this page
  1. Small talk is detected first
  2. What small talk gets
  3. Short factual questions
  4. When you want a second opinion on something simple
  5. Why this matters for credits

Small talk is detected first

Keplar checks whether a message is plain social chat before it classifies anything else. The check is conservative and works on whole phrases: greetings, thanks, "how are you", goodbyes, "who are you", and short acknowledgements, up to 60 characters and 8 words.

Anything with a question, a request, digits, code or links, attachments or media, or a mode switched on is not small talk and goes through the full engine.

What small talk gets

  • One free model, with a fallback to other free models and finally a static line.
  • A short reply (capped at about 160 tokens).
  • No panel, no verifier, no judge, no comparison section.
  • No credits on any plan.

The reply is shown as plain text, without the consensus ring or the six sections.

Short factual questions

A short, plain lookup such as "What is the capital of Australia?" is classed simple and goes to one fast model. There is no review step, and the answer says "No cross-model verification needed for this question."

If the question needs an exact figure, a count, or arithmetic, it is not left to one model; see Exact checks.

When you want a second opinion on something simple

Choose Most thorough in the options next to the composer. Simple questions then get a panel too. Or rephrase the question as a decision ("Which of these is more likely and why?"), which the classifier reads as analysis.

Why this matters for credits

Casual messages cost nothing, and simple single-model answers are cheap, so the credits you pay for go to the questions where a panel helps. See Credits explained.

Related

  • How Keplar understands a question: The classifier that decides task type, complexity and needed capabilities, what signals it uses, and why it is a transparent rule set rather than another model.
  • Which questions use more models: A practical guide to what makes Keplar consult one model, three, or five: question type, length, stakes, forecasts, attachments, Deep Research and thoroughness, with examples.
  • Credits explained: What a Keplar credit is, what costs more or less, how credits are counted from real provider charges, and what does not use credits.
PreviousSources, citations and web lookupsNextWhy consensus can be wrong

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On this page

  1. Small talk is detected first
  2. What small talk gets
  3. Short factual questions
  4. When you want a second opinion on something simple
  5. Why this matters for credits