Free Tool
What is the cheapest thingthat can make this decision?
Not which model is smartest — which level is sufficient. Eight questions about one task, and it lands on deterministic code, a decision model, a fast general model, a frontier reasoning model, or a person. Two gates can push it toward a human and never away from one, because a decision you cannot grade is one you cannot automate.
Loaded with a support-ticket routing task so you can see a finished result. Change any answer, or clear it and start from your own.
The cheapest sufficient level
Level 2 — Decision model
Classification, scoring, routing, gating, ranking — a typed answer software acts on.
Fix first
Nothing. This task is already at the cheapest level that can do it, it is gradeable, and its failure mode is covered. There is nothing here to change.
Both gates
- clearGround-truth gate
- clearIrreversibility gate
The ladder
- L1Deterministic code — Known rules, arithmetic, validation. No model, no per-call cost, no drift.
- L2Decision model — Classification, scoring, routing, gating, ranking — a typed answer software acts on.
- L3Fast general model — Moderate reasoning and text generation where the answer space is open.
- L4Frontier reasoning model — Complex planning, analysis and synthesis across many connected facts.
- L5Human judgment — High-stakes calls, exceptions, and anything nobody can grade.
Nothing you answer leaves your browser. There is no upload and no request — the eight answers are scored on your own machine, which is also why the same answers always give the same level.
Why the ladder, and not a model comparison
Most AI buying decisions get framed as a contest between models, which is the wrong contest. A task that a formula settles should not call a model at any price; a task that has to write a document cannot be a typed decision however cheap typed decisions become. The level is a property of the task, not of the vendor — so the useful move is to place the task first and shop second. Where a task lands two levels above where it could sit, the gap is usually the answer space: bounding it is the largest single cost and latency drop available.
Common questions
What does the Decision Fit Check do?
It places one task on a five-level ladder — deterministic code, a decision model, a fast general model, a frontier reasoning model, or a person — and, where something is short, names the single change that would move it down a level. It answers the useful question, which is not which model is smartest but what is the cheapest, fastest, sufficiently capable intelligence for this specific decision.
Why would I not just use the best model for everything?
Because the best model is the slowest and most expensive one, and most tasks inside software are not reasoning problems. Routing a ticket, scoring a lead, or flagging a transaction is a decision with a known set of valid answers. Sending that to a frontier model costs more, takes longer, and returns prose your code then has to parse back into the value it wanted.
What is a decision model?
A model built to return a typed value rather than text — a choice from a fixed list, a score on a known scale, or a probability that something is true. Software acts on the value directly with no parsing step. TypeSafe AI's Jev is the current example, which is what made this distinction worth a tool.
Why does it refuse to automate some tasks at all?
Because of the ground-truth gate. If two competent reviewers could not label 200 examples and agree on the answer, there is no measurable right answer — so there is nothing to check a model against, at any level. A decision you cannot grade is one you cannot measure, and one you cannot measure is one you cannot safely automate. That verdict is the honest one even though it is the expensive one.
What is the second gate?
Irreversibility. If a wrong answer cannot be undone and nobody sees it before it takes effect, the task routes to human judgment whatever a model would score. Cheap decisions become dangerous precisely when they become numerous — a small error rate over a large volume of irreversible actions is a lot of unrecoverable outcomes.
Can a gate ever make the answer cheaper?
No, and that is deliberate. Both gates are worsen-only: they can move a task toward human judgment and never away from it. The tool can refuse to automate something; it can never bless automating something it has not been told is safe. That direction is the whole safety property.
Does this send my task description anywhere?
No. There is no free-text box and no upload — you pick one of three answers to each of eight questions, and the scoring runs in your own browser. Nothing is transmitted, stored, or logged. That is also why the result is reproducible: the same eight answers give the same level every time.
It says level 2 but gives me no fix. Is that a bug?
No. When a task is already at the cheapest level that can do it, is gradeable, and has its failure mode covered, there is nothing to change and the tool says so. Naming a fix on a clean result would be telling somebody with a working setup to go and repair it.
Where to go next
If this lands at level 2 and you are about to install a third-party server or skill to get there, the MCP Server & Skill Trust Gate grades the artifact before you install it. If the question is what the decision layer will cost once it is everywhere, the Token Economics Workbook prices it per outcome rather than per token.