Ask in English or Danish. Every reply shows its live compliance: which
policy it used, whether the answer is grounded in that policy, and when it declines rather than
guess — built on friction theory.
Rule-budget RAG · grounding audit · selective abstention · topic-routed hand-off — on a small open model (Qwen2.5-7B).
This is a synthetic handbook with deliberate gaps (no parental-leave or pension policy).
The point: the assistant must decline and refer when the answer isn't in the handbook — not
invent one. Watch it follow the relevant policy, ground its answer, and admit what it doesn't know.
What it can and can't guarantee — and how to get the best out of it. It does the
verifiable part with certainty: every turn shows which policy it used, whether the answer is
grounded in that policy, and it declines and refers when the handbook doesn't cover the
question — auditable end to end. It cannot vouch for the rules themselves (a wrong policy,
perfectly followed, is still wrong) — it only knows the handbook it is given. To get the best out of
it: keep the rule-set small and non-competing, retrieve the relevant rule rather than
dumping the whole book, and size the model to how many rules actually compete per turn — the
"optimal, not perfect" discipline (more rules → lower adherence, including on the safety-critical ones).
Try a question the handbook can't answer (parental leave, pension) and watch it abstain.