# Guided verified weighting in WFC 2.0

`wf_autoweigh()` gives survey researchers a narrated path over the verified engines. It no longer builds a target from raw runtime data. Prepare `design`, import `target`, and declare `dims` first.

    guided <- wf_autoweigh(
      design,
      target,
      dims,
      method = "raking",
      trim = NULL,
      interactive = FALSE,
      lang = "en"
    )

    guided$weights
    guided$diagnostics
    guided$ledger

The ledger uses stable English programmatic keys while its `detail` text may be localized. Artifacts align with ledger rows so a statistician or agent can inspect each precheck, recommendation, and report.

Automatic mode chooses only from declared safe settings. It does not inspect outcomes, change the target, widen bounds, or manufacture approval.

    wf_report(guided$weights, audience = "decision", lang = "zh_CN")
    wf_report(guided$weights, audience = "statistician", lang = "en")

For production, prefer `wf_plan_weights()` plus separate `wf_approve_plan()` and `wf_execute_plan()` so human approval is bound to one immutable plan.