The context sets, the packaged knowledge bases and the example bundles are
replaced by one fictitious example set about IT operations in an invented
organisation: three context sets (serverrom-2027, driftsavtale-2027 and the
two-base drift-og-avtale-2027), two synthetic knowledge bases under
src/portfolio_optimiser/data/kunnskapsbaser and two example bundles under
src/portfolio_optimiser/data/bundles. Numbers, codes and structural values in
tests and fixtures are kept; names, ids and wording change. Dated measurement
documents that only recorded runs on the replaced material are deleted.
Gate figures measured on the new set are not comparable with earlier ones.
The exclusion gate from the previous commit is green: 0 tracked files hit
outside the shared/ subtree.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
generate_via_llm consumed each validator Rejection internally (`last`), fed it into the
next attempt's prompt, and dropped it. So Step 5 was real but unobservable: a caller could
see THAT a proposal validated, never that it validated on attempt 2 after the deterministic
validator falsified attempt 1. It was the one step of the eight with no output to show.
The seam is a typed return value -- GenerationResult(outcome, refinements) -- rather than an
out-parameter or a callback: a returned value cannot be silently lost by a caller that forgets
to pass a collector, and mypy forces every call site to acknowledge it.
refinements carries ONLY rejections that were actually fed back. When the attempt budget runs
out the final rejection IS outcome; counting it here would be double-counting, and the bounded
control test goes red on the collect-everything implementation that gets this wrong.
The loop's bound is untouched: max_attempts and meter.tick_round stand, and `last` still drives
the prompt alone, so prompt growth is unchanged. run.py accumulates across _evaluate calls, so
_evaluate_mandate is untouched; RunResult.refinements defaults (the coverage precedent) and is
concatenated across approaches rather than keyed per approach -- stated as an honesty limit.
The simulation now shows it: the scripted proposer overclaims 250000, which the validator
falsifies against P90 = 90000, and the corrected 30000 validates. Only the overclaim is
scripted -- the rejection is computed. scripted_factory takes a per-role reply selector so this
needs no second scripted client body.
README records the two accuracy changes only (Step 5 is now inspectable; the simulation trace
shows the correction). The level-2 publishing claim stays deferred until after the demo (O4).
Load-bearing MEASURED against the full suite with a control, four mutations all red:
detach the returned history (4 tests) - collect-everything (control only) - detach the run
wiring (2 tests) - revert the simulation's proposer to a constant (the demo-protection test).
Control: 759 passed / 4 skipped; ruff, format and mypy clean.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_017CcWFcREUi6YPjEpN3ACDP
