oto.cx
jev

typesafe

jev.

Ask Jev typed questions about one state and get answers with probabilities.

add to otoauth : —prefix : jev_*

setup & usage

⚠ a shared OpenRouter API key: the tenant's, or the instance's platform key

jev is a TypeSafe model served by OpenRouter: the key is an OpenRouter API key (starts with sk-or-), not a TypeSafe key — there is none. It is a shared key: either the tenant's, set once for all its organizations, or a key set at the platform level of the instance and granted to the organizations it serves.

  • use a dedicated key with its own spend cap: the same key elsewhere opens OpenRouter's whole model catalog
  • a key set on an organization, team or person is not used and shadows the shared one: the tool refuses it and names who must remove it
  • no key, no call — there is no free tier
  • the state goes to a third party (OpenRouter, then TypeSafe), as a subprocessor of whoever set the key (the tenant, or the instance for a platform key)
    • ▸ triage a batch with one rubric

    jev returns a typed answer with its probability, never text: yes/no (noul), a choice among options (choice), a position on an ordered scale (score). It pays off on batches: a single case the agent can judge itself does not need jev.

  • "qualify these 200 profiles before I enrich them" → jev_items: one rubric, N states, nothing written; a batch that runs out of time (~40 s) returns what was answered and, in retry, the states to send again
  • "qualify every row of this table" → jev_rows: the server reads, judges and writes back (answer, <col>_p confidence, model); only rows with an empty model_column, so a re-run resumes; dry_run on known cases first
  • a whole table (hundreds of rows or more) → jev_rows(background=true) after the dry run: one call returns a job_id, the server judges every matching row itself, slice by slice; follow it with jev_job(op='status') every minute or so, stop it with jev_job(op='cancel'). A dropped connection doesn't stop it; a revoked key or a spent quota does, at the next slice (what was judged stays written and billed). One active job per table and model_column
  • jev_rows creates missing output columns (choice → enum of its criteria, score/noul → number, plus <col>_p and model_column); an existing column is never changed, and a type mismatch is refused
  • "does this row match my target?", tuning a rubric before a batch → jev_ask with the row's state and a noul
  • a state fits in 16 KB of JSON: only the fields the judgement needs, never the whole record or document
  • put the whole rubric in one call: questions are answered in parallel, the state is billed once, each extra question costs ~48 tokens
  • questions in one call cannot see each other: a dependent question needs a second call
    • · reading a probability, and where to set the threshold

    A probability near 0.5 means "as likely as not", never "medium".

  • validate fit against known outcomes before trusting it; combine Jev's answers with structured fields in plain code
  • keep two thresholds and send the middle band to a human or a text model: cheaper than forcing a label
  • confidence describes how concentrated the distribution is, not how safe the next step is
  • a choice ALWAYS answers, even when the question does not apply: read the filtering noul first, or add a "none" option and check its probability
  • the response names the exact model: store it next to the answer, it makes a threshold reproducible
    • · cost

    Only input is billed, output is free, and every response carries usage.cost, the real cost in dollars — that is what gets billed, not a call count.

  • a short state (a table row, a profile) costs a few dozen micro-dollars
  • a state is capped at 16 KB of JSON (upstream context goes to 32,000 tokens)

    • outils

    chargement…

    usage

    claude code — install the oto plugin — claude plugin marketplace add otomata-tech/oto-plugin — mcp + skill configured.
    claude.ai — add mcp.oto.cx/mcp as a custom connector (guide)
    cli — pipx install oto-cli then oto jev …
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