llm-ingestion-okf/docs/2026-09-07-okf-konsumskill-maaling.md

The consumption pre-pass, measured — hit@8 on a 629-concept bundle

Date: 2026-09-07 · Instrument: tools/okf_consume.py at 51735fa, scored by tools/okf_consume_measure.py · Corpus: a 629-concept, 39-document OKF v0.2 segmented bundle built by this library's own doors on 2026-09-03.

This is the first time docs/consumption-contract.md has been run against a bundle. The contract has existed since S5 with no instrument, and a rule with no instrument is a rule nobody can be shown to have broken. What follows is that instrument's first numbers, with the two things a first number needs: the denominator it was measured over, and the chance baseline it should be read against.

Read the headline with its granularity attached. The order this work came from asked for "≥ 5 spørsmål der fasit-konseptet er kjent" — gold at concept granularity. The operator answered the open question on it (2026-09-07 04:33Z) with option (a): gold is the top-level document the question names, taken from the corpus's own document titles and never from anything the ranker computes. Five of the six rows below are therefore DOCUMENT-granularity, which is a weaker claim than the order asked for. One row — the price form — has a gold document holding exactly one concept, so document and concept granularity coincide there, and it is the only concept-level result in this report.

The result

figure	value
questions	6 positive + 2 known-negative controls
hit@8	5 of 6, every hit at rank 1
expected by chance	1.35 of 6
denominator	629 concepts per question, every one accounted for
k	8
known-negative controls	2 of 2 FAILED — see below
spent per question	17 970 – 74 838 bytes (median 20 182), limit 120 000
whole payload per question	109 951 – 165 109 bytes
wall time per question	0.51 – 0.56 s (629 concepts, 1.95 MB of concept text)

Five hits at rank 1 against an expectation of 1.35 is a real signal and a small one: n = 6. Nothing here supports a claim about the ranker's behaviour on a seventh question, and this report makes none.

Per-row, with the baseline each row must be read against

The per-question gold ids are not in this file. They name documents in a consumer's corpus, and this repository keeps corpus paths and document titles out of tracked files; they live in the local project directory beside the run, and go to portfolio-optimiser by coord. What is publishable is the shape:

row	gold concepts	hit@8	rank	chance, analytic	chance, empirical
1 — the concept-level row	1	✅	1	0.013	0.013
2	49	✅	1	0.479	0.483
3	20	✅	1	0.229	0.231
4	43	✅	1	0.434	0.438
5	11	✅	1	0.132	0.134
6	5	❌	—	0.062	0.063

Why every row carries its own baseline. A document-prefix hit is easier for a large gold document: with gold sets spanning 1 to 49 concepts, a raw count of 4/6 could be produced by a ranker that had learned nothing. Row 2 alone is 48 % likely by chance; row 1 is 1.3 %. The two hardest rows (1 and 6, at 0.013 and 0.062) are one hit and one miss.

The empirical baseline is 20 000 draws at seed 20260907. It agrees with the analytic form to within about half a percentage point — not to three decimal places, and this report does not claim it does.

The miss, diagnosed rather than absorbed. The gold's best concept ranked 11 overall, just outside k = 8, and comes back at rank 11 for k = 12 and k = 16. Cause: the profile matches two tokens when they share four leading characters, so a compound question term matches two much larger sibling documents in the same subject area, and those two fill all eight slots. The document prior does not rescue it (0.333 against 0.433 and 0.415). This is a near-miss at the reported k, not an absence — and it is the shape of failure to expect from this ranker: crowding by large same-prefix neighbours.

The controls that failed, stated first rather than last

The order required a known-negative: a question with no answer in the bundle must produce an empty or "not found" payload, never a confident guess. Both known-negative questions produced eight excerpts. The control failed.

control	tokens reaching nothing	delivered
the question chosen as planned	2 of 6	8
the most lexically disjoint question found	4 of 6	8

Why, measured rather than guessed. The pre-pass has a per-concept relevance rule (no_lexical_match) that withholds a concept the question does not reach, and it works: it fires on 600-odd concepts per run. It does not work as a whole-question gate, because no natural Norwegian question is lexically disjoint from a 629-concept corpus under a four-character shared-prefix rule. Measured per token: the interrogative hvor reaches 40 concepts, mange 17, brukes 83, etablert 38. Four candidate questions were probed and none reached zero on every token. The first control's content words did genuinely match — one of them reached 17 concepts describing welded seams in floor covering, which is a correct lexical answer and a useless topical one.

Consequence for anyone using this, stated in the skill as well as here: an empty excerpts list is evidence of absence; a full one is not evidence of presence. When the delivered excerpts do not answer the question, the right output is [sourced-not-sufficient] plus a statement that the cut found nothing responsive — not eight answers.

What would fix it, named and not built. Rarity weighting: a token matching a large fraction of the corpus carries little information, and requiring a delivered concept to match at least one informative token would make the gate work. Smoothed IDF is on the plan's own list of mechanisms worth lifting and this build does not implement it. It is not attempted here because this step's scope fence freezes the instrument before it is measured — tuning a ranker against the questions it is being scored on produces a number about the tuning.

Rarity weighting, measured before being built — the named mechanism does not exist

Date: 2026-09-07, follow-up order 20260907T074541Z-939882634-from-.claude. The order named a specific mechanism — smoothed IDF over the corpus the walk already reads, gating no_lexical_match so a delivered concept must match at least one informative token — and required both known-negative controls above to reach delivered == 0 on the real K2 bundle. This is a refutation sweep, not a tuning sweep: every threshold in the full observed range is reported, not a value chosen to pass. No threshold was picked to make the negatives zero; the table below is what falsifies that a passing threshold exists at all, and the order is returned on that basis rather than implemented.

Method. idf(t) = ln((N+1)/(df(t)+1)) + 1, N = 629. df(t) counted with the same four-character prefix rule tokens_match already applies (the instrument okf_consume_measure.token_reach already uses), over title + concept-id + body across all 629 concepts. For every concept, M is the highest idf among the question tokens that concept matches at all (or none, if the concept matches nothing). A candidate threshold T keeps a concept only when M > T. Swept T from 1.5 to 7.9 in steps of 0.1 — the corpus's full observed range for these two questions' tokens.

T	neg1 (sveising) passing	neg2 (pingviner) passing	gold hits still reachable (of 6)
1.5 – 2.5	31	49	6
2.6 – 3.5	31	49	4 (brann, branntegninger lost)
3.6 – 3.7	31	49	3 (akustikk lost)
3.8 – 4.2	31	17	3
4.3	31	17	2 (solcelle lost)
4.4 – 4.5	31	17	1 (prisene only)
4.6 – 5.0	14	0	0
5.1 – 6.0	5	0	0
6.1 – 6.3	2	0	0
6.4 – 7.9	0	0	0

The frontier is empty, and it closes from the wrong side. neg2 first reaches 0 at T = 4.6 — and at that exact same T, gold-hit reachability has already fallen to 0 of 6: no positive question's gold document is reachable any more. neg1 has not moved yet at T = 4.6 (still 14 concepts passing — titan idf 6.059, vakuum idf 6.347, reglene idf 5.048, sveising idf 4.555: the two rarest tokens in the entire gold set belong to the sveising question, so rarity weighting scores them as maximally informative) and does not reach 0 until T = 6.4, by which point gold-hit reachability has been at 0 for eighteen threshold steps. There is no T where both controls read 0 while any positive question still reaches its gold document — the interval where neg2 is satisfied and the interval where neg1 is satisfied do not overlap, and the positive constraint is already violated before either control interval begins.

Why, structurally, not just numerically.

1. df measured over the colliding matcher measures collision breadth, not rarity. The four-character prefix rule that lets varene match varemottak also collapses every brann* compound into one bucket: brannkonseptet reads df=132, reaching 18 of the corpus's 39 documents, because brannalarm, branntrapp, branncelle and branntetting all share the same four leading characters and none of them is the same word. Rarity weighting inherits this pollution rather than fixing it — the most topical word in the corpus for the brann question reads as the least rare.
2. MIN_TOKEN_LENGTH = 3 admits tokens MIN_SHARED_PREFIX = 4 guarantees can never match. hva, for, den are three characters; tokens_match requires the shorter side to reach the four-character floor before any comparison runs, so these tokens are structurally df = 0 regardless of what the corpus contains. The brann question therefore rests on its single remaining token (brannkonseptet) the moment sier — which matches three concepts, none in the gold document — is set aside.
3. The sveising question's match is a real word, not noise. sveising matches sveisede in eight architectural-drawing concepts describing welded floor-covering seams — correct lexically, unrelated to the question's actual subject. No token-rarity statistic distinguishes this from a genuine topical match, because by the rarity measure it is one (df = 17, concentrated in a single document, doc_reach = 1/39).

What is not built. A coverage rule — require two or more informative tokens to match, rather than any one — probably zeros both controls, since neither negative question has two tokens that jointly land in the same small concept set. It is named and explicitly not implemented here: choosing it now would be picking a mechanism because it was checked against these two answers, which is exactly what this order's own fence forbids. It goes to the operator as an option, unmeasured.

Honesty limits

Six, and the first three matter most.

1. n = 6. Six questions is a small sample and the table says so on every reading. The chance baseline is what keeps it from being meaningless, not what makes it large.
2. The question texts were written after the ranker existed. The plan fixed the gold documents' size profile before any ranker existed — its recorded per-row baselines sum to 1.35, and the sizes used here reproduce that total exactly, which is an independent check that this is the gold set the plan profiled. But the plan recorded no question texts, so those were written during execution. Three of the six gold documents also could not be pinned uniquely from the recorded sizes and were chosen among equal-sized candidates. The gold documents themselves came from the corpus's own titles, per the operator's answer, and not from anything the ranker computes — but this is not a blind evaluation and must not be quoted as one.
3. One ranking change was made with a gold answer visible. The stage-one document prior originally summed lexical overlap across a document's units, which measures document size: measured on this corpus, a 79-concept document scored 6.0 (0.076 each) against the price document's 2.0 over 1 concept, and the price gold fell outside the top 8. The prior is now a density. The fix is justified by the scoring function's own arithmetic rather than by the answer — a prior that grows with size is measuring size — but it was found by running row 1, and the ranker is therefore not blind to that row.
4. Five of six rows are DOCUMENT granularity, not the concept granularity the order asked for. Row 1 is the exception and is labelled throughout.
5. Two of the three states this contract makes consumers distinguish have denominator zero in this corpus. adjudicated never occurs (all 618 present values are proposed; 11 concepts carry no key and read as unknown), and verified is absent on all 629 — anchored and unanchored — so every excerpt is unverified. type: verdict is likewise absent on all 629, which makes the § 9.1 exclusion vacuous here. All three are exercised only against a synthetic fixture, and the skill states that rather than implying coverage.
6. The contract checker is a lint, not the acceptance. Measured: it returns 0 findings on a payload declaring considered=0, withheld=0, delivered=0 paired with the unfilled template. A green checker means the payload carries what a claim would have to rest on — not that the claim is sound. The real gates are the negative controls, the partition assertion, the placeholder scan and the digest test, and none of those is something the checker performs.

What the contract's own gates reported

gate	result
SS 5.2, considered == withheld + delivered	closes on every run, by construction
SS 5.3, every withheld concept names its rule	621 of 621 on the row-1 run, from a closed set of six
SS 7.4, the instrument reproduced a known-positive before reporting	10 349 expected, 10 349 measured, plus a second route (wc -c = 10 060, delta 289)
SS 7.2, spent is the delivered set	74 838 spent against a 120 000 limit on row 1 — where a whole-payload reading would have put 165 109 against the same limit and refused
SS 3.3, the ref is a content identity, not a declared version	sha256-tree: over the reachable tree; --ref asserts and never overrides
SS 9.2, no directory enumerated	the index walk reaches 629 concepts, exactly the set the forbidden method finds
contract check on a real payload	conformant: 14 rules over 8 excerpts and 621 withheld entries, 0 findings, exit 0
negative control: broken identity	NOT conformant, 2 findings, exit 1
negative control: missing payload	exit 2

Reproduce

# One payload, and the checker on it.
.venv/bin/python tools/okf_consume.py <bundle> \
  --question "Hvordan skal prisene fylles ut?" --out payload.json
.venv/bin/python tools/okf_contract_check.py \
  --skill skills/okf-consume/SKILL.md --payload payload.json

# The whole table. The gold set is an INPUT and is not in this repository.
.venv/bin/python tools/okf_consume_measure.py <bundle> --questions <gold-set.json>

The gold-set file's shape is in tools/okf_consume_measure.py's module docstring. Determinism is asserted by the suite, not by inspection: two runs of the same (bundle, question, k, limit) produce byte-identical output, and the module reaches no clock.