pulse_analyze
Estimate a causal effect from a dataset and answer a business question. Provide exactly one of ``csv`` (CSV text) or ``data`` (list of row objects). Returns the full long-form Pulse report (the same answer an email reply contains) as the primary text content and as ``report`` in the structured result, followed by chart PNGs as image content blocks (unless ``include_charts`` is false). Structured fields: the adjusted effect size (``ate``/``effect_size``) with its confidence interval (``ci_low``, ``ci_high``, ``ci_range``), per-channel effects (``channels``, keyed by outcome), confidence, and caveats. A ``test_design`` (how long a spend-cut test would take to confirm the effect, and whether the data already suffices) is included only when the question asks about sample size, power, or how long a test would take, or when ``include_test_design`` is true; otherwise it is null. With ``include_guardian_verdict`` it also returns ``guardian_verdict`` ``{verdict: pass|caution|hold, reason}``, computed locally. All numbers are deterministic statistics, never LLM-generated. Args: question: The business question, e.g. "Does ad spend drive sales?". csv: Dataset as CSV text. data: Dataset as a list of row records (alternative to ``csv``). cause: Treatment column (inferred from the question if omitted). effect: Outcome column (inferred if omitted). confounders: Columns to adjust for, in addition to those discovered. outcomes: Several outcome columns, for by-channel effects. time_col: Time column (used for the test-design cadence). include_guardian_verdict: Also return a pass/caution/hold verdict. include_charts: Attach chart images (DAG, effect, trend) as image content. include_test_design: Force the spend-cut test design / sample-size section on (true) or off (false). Omit (null) to include it only when the question asks about sample size, statistical power, or how long a test would take.
csvdatacauseeffectoutcomesquestion必填time_colconfoundersinclude_chartsinclude_test_designinclude_guardian_verdict