get_forecast

shallow

com.ask-ai-data-connector/ask-ai · Verify this server

Forecast a metric — answers 'what should I expect?' / 'are we on track this month?' / 'project next month'. Returns a per-store `stores` array (each in its OWN currency — never summed across currencies). Each store has: `currentMonth` (month-to-date actual + projected month-end with low/high band, built from the live daily run-rate), `horizon` (future full months with expected/low/high), `method`, `confidence`, explicit `assumptions`, `historyMonths`, and a ready-to-render `charts[0]` line spec (seriesField='series' splits actual vs forecast). HONESTY: every forecast carries a method (month_to_date_pace / linear_trend / naive_last_month / yoy_seasonal), a confidence level, and an interval — LEAD with the range and the confidence, never present the point estimate as a promise. Current-month projection works immediately from orders; forward months need calendar-month snapshot history and degrade gracefully (low confidence / declines to project when too thin). v1 metrics: revenue, orders.

100.0/100

1 trials · measured 8 days ago

get_forecast scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against com.ask-ai-data-connector/ask-ai, measured 25 Aug 2026 under methodology v0.2.0. Every measured component scored 100.

Component breakdown

ComponentWeightValue
Reliability35%not applicable
Schema integrity25%100.0
Failure behaviour15%not applicable
Latency15%not applicable
Concurrency10%not applicable

Tool details

Transport
remote
Credential class
gated
Category
Commerce & retail
Input schema
not declared
Output schema
not declared
Side-effect classification
unclassified

Score history

DayScoreTierMethodology
2026-08-25100.0shallowv0.2.0

Probe evidence

ProbeOutcomes
schema_integritypass: 1

Raw request/response logs are not archived yet — the outcome counts above are drawn directly from every recorded trial.

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Vouch score: get_forecast
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get_forecast — Vouch