Probabilities and confidence
How to read strike-1 probabilities, confidence, confidence_band, and meta.
Every strike-1 answer includes a probability on every option, read directly from the model (prob_source is "native"). These are real probabilities (beta, not yet calibrated): use them to compare options and route work, not as forecasts.
Reading the distribution
import strikeflow as strike
result = strike.decide(
"Which team?",
["billing", "tech", "sales"],
context="Please refund the duplicate charge on my card.",
)
for option, prob in result.probabilities.items():
print(option, round(prob, 4))
assert abs(sum(result.probabilities.values()) - 1.0) < 1e-5Use probabilities to:
- Route only when the margin is clear.
- Send ambiguous cases to a human or a general LLM fallback.
- Log decision quality in traces.
Confidence
confidence is the probability mass on the chosen answer. If the API omits it, the SDK sets confidence = probabilities[answer].
if result.confidence < 0.7:
# your fallback: ask a human, call a general LLM, or re-prompt
...confidence_band
On the raw /v1/systemone response, each answer may include confidence_band: "high", "leaning", "low", or null when the model cannot assign a band. Use it for coarse routing; use confidence for numeric thresholds.
The strikeflow SDK maps the HTTP response into DecisionResult; inspect result.raw if you need confidence_band or meta from the API.
meta
The top-level meta object on a systemone response includes latency, region, and related fields. Use it for observability, not as a user-facing accuracy score.
low_confidence flag
Pass min_confidence on decide or configure the engine once:
import strikeflow as strike
strike.configure(min_confidence=0.7)
result = strike.decide("Escalate?", "yes_no", context="vague message: hmm")
if result.low_confidence:
...The flag is computed client-side: (result.confidence or 0) < min_confidence.
Tool results
strike_decision_tool().handle(...) returns a JSON dict (via DecisionResult.to_dict()) with rounded probabilities, confidence, low_confidence, and trace_id when tracing is active.