# The interface's first experiment: does the portrait earn its place?
#
# This tests DELIVERY, which this interface owns. The competition about which
# editorial voice travels belongs to the campaign and is run on the per-variant
# engagement this interface reports — see docs/observation.md.
#
#   fluid experiment design --file experiments/E-tg-delivery.yaml
#   fluid experiment start E-tg-delivery --generation 2 \
#     --default-revision R-2 --policy-out rp.json
#   fluid policy put --file rp.json
fluid_experiment:
  schema_version: "0.1"

  id: "E-tg-delivery"
  interface_id: "helix-forge-telegram-publishing"

  hypothesis_refs:
    - "H-tg-visual"
    - "H-tg-textonly"

  # R-2 attaches the portrait, R-3 publishes text only. Neither is an
  # incumbent: R-1 publishes without either treatment being settled, so this
  # is a comparison between two answers rather than against a baseline.
  control_revision: "R-2"
  candidate_revisions:
    - "R-3"

  cohorts:
    - "telegram-subscribers"

  allocation:
    control: 0.5
    candidate: 0.5

  # An even split because there is no incumbent to protect. The usual 90/10
  # caution limits exposure to an unproven candidate; here both arms are
  # equally unproven and the scarce resource is posts, not safety.

  metrics:
    primary:
      - "engagement_rate"
    guardrails:
      - "unreviewed_publication"
      - "missing_source_attribution"
      - "missing_subject_consent"
      - "error_rate"
    secondary:
      - "source_link_rate"
      - "forward_rate"
    learning:
      - "time_to_first_view"

  start_conditions:
    - "both revisions verified against the private test channel"
    - "channel has at least 100 subscribers"

  stop_conditions:
    - "hard_guardrail_violation"
    - "unreviewed_publication"
    - "manual_stop"
    - "max_duration_reached"

  max_duration_hours: 2160  # 90 days

  result:
    state: "PLANNED"
    preferred_revision: null
    evidence_refs: []