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
Operator feedback: fagpersoner must be able to name the approaches a run shall
evaluate for a project, and/or ask the system for its own. Today the hypothesis
prompt is hardcoded ("Propose ONE concrete cost-saving measure") and the only
expert-facing lever, --dimension-config, FILTERS what may pass the scoping gate
rather than DIRECTING what is spent attempts on. This is the input that was
missing.
`mandate.py` is the typed commission + a fail-fast loader (mirrors
`load_dimension`/`load_goal_config`): missing or malformed refuses, because a run
must never proceed on a silently degraded commission — the coverage report would
then describe work nobody ordered. Stdlib + pydantic only, so it joins
`_MAF_FREE_MODULES` and can be mirrored to the D7 sibling.
Two refusals carry real defect classes: an EMPTY commission (no approaches and no
own proposals) is a caller error, not a result; and a duplicate approach id — or
one claiming the reserved OWN_PROPOSAL_ID — would collapse two coverage rows onto
one key (the S3.2 key-collision class), which is exactly the silence the coverage
report exists to prevent.
The numeric target is deliberately NOT duplicated here: it already lives in
GoalContract, and two copies of one number drift apart ((p) precedent). The
mandate carries intent; `announce` merely restates the figure.
`_build_messages(approach=...)` switches the opening instruction from *find one*
to *quantify THIS one*, carrying the expert's label and description VERBATIM —
the description is the reason the approach is worth trying, the one part the model
cannot infer from cost data. `approach=None` is byte-identical to the previous
prompt, so every existing run and golden is untouched.
The gate is unmoved: `validate_proposal` is called exactly as before. A
commissioned approach gets no discount — the expert directs what is EVALUATED,
never what is APPROVED.
Load-bearing MEASURED against the whole 695-test suite, four mutations all red:
detach the approach injection (2 red, control stayed green) · let a commissioned
approach bypass the validator · make the mandate loader tolerant · drop the
empty-commission refusal.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ULCqjLF61rehj5cZmdUoR3
