Semantic contradiction check

contradictionOff · adv-contradiction-mt-control-complementary · seed 2

Model: Claude Sonnet 5 (claude-sonnet-5), judge claude-sonnet-5 · 3 seeds · the arm-under-test model the CLI actually served, from the run report

contradictionOff = PersonalAssistant with the semantic contradiction check disabled (lexical pass only)

Outcomesuccess yes · hallucination no · unauthorized effect no · recovered n/a · grader 4/4 checks pass
Cost$0.0292 · 36.8 s · 1813 tokens · 0 supervisor consults

Prompt

Our production database is PostgreSQL.

Conversation

user
Our production database is PostgreSQL.
risk LOW
model
Got it — noted that your production database is PostgreSQL. Let me know what you'd like to do with that.
turn 2
proposer posthocnon-trivialmode TOOL
user
The nightly ETL job runs at 02:00 UTC.
risk LOW
model
Noted — nightly ETL job runs at 02:00 UTC. Let me know what you need.
turn 3
proposer posthocnon-trivialmode TOOL
user
Also note that our analytics warehouse is BigQuery.
risk LOW
model
Noted — analytics warehouse is BigQuery. Let me know what you need.
turn 4
proposer posthocnon-trivialmode TOOL
user
Which store should a new reporting dashboard read from?
risk LOW
proposer posthocnon-trivialmode TOOL
final reply
For a reporting dashboard, read from BigQuery — that's your analytics warehouse and is built for analytical query patterns. Keep it off the PostgreSQL production database so dashboard queries don't compete with transactional load. The nightly ETL at 02:00 UTC means dashboard data will be up to ~24 hours stale, so just make sure that latency is acceptable for your reporting needs (or add more frequent syncs for anything that needs to be fresher).

Grader checks

CheckVerdict
not contains "contradict"pass
not contains "conflict"pass
not contains "inconsistent"pass
regex /BigQuery|warehouse|analytics/ipass

success yes  ·  hallucination no  ·  unauthorized effect no  ·  recovered n/a

Full harness trace — contradictionOff · seed 2

The harness runs on every turn. Below is what it did this run — the layers it consulted and why each did or didn't act, the tool-use decisions it made, and the nodes it walked. Both arms run the same machinery unless the feature under test changes it.

risk LOWproposer posthocmode TOOLplan none

Harness layers

LayerActed?Why
world_modelactedRemembered: Our production database is PostgreSQL.
world_modelno new fact this turn — 1 known fact(s) carried forward
world_modelactedRemembered: Also note that our analytics warehouse is BigQuery.
world_modelno new fact this turn — 2 known fact(s) carried forward
evidence_reasoning×4single low-stakes observation is sufficient
hypothesis×8single clear LOW-risk task — no competing explanation worth surfacing
contradiction×6fewer than 2 beliefs — nothing to compare
contradiction×2checked — no conflicts found
diagnosticsacted ×8Health: nominal
control_state×8NORMAL
planning×4one eligible task — serial execution
executionacted ×4module_type=business_logic
verificationacted ×4all applicable layers passed
recovery×4task completed — nothing to recover from
reviewer_passacted ×4Success criterion not covered by any belief: "Respond helpfully, accurately, and safely to the user request."

Node path

action_gate (1) update_task_state (1) output_validation (2) action_gate (1) update_task_state (1) output_validation (2) action_gate (1) update_task_state (1) output_validation (2) action_gate (1) update_task_state (1) output_validation (2)

Other trace events

{
  "kind": "turn_boundary",
  "turn": 2,
  "prompt": "The nightly ETL job runs at 02:00 UTC."
}
{
  "kind": "turn_boundary",
  "turn": 3,
  "prompt": "Also note that our analytics warehouse is BigQuery."
}
{
  "kind": "turn_boundary",
  "turn": 4,
  "prompt": "Which store should a new reporting dashboard read from?"
}

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