The constant was detach-proof but value-unproven: mutating 6 -> 4 left all 628
tests green, so nothing held the figure to the claim it carries. Measuring what
actually constrains it gave a narrower answer than the premise assumed — 6 -> 4
CANNOT be made red without inventing a resolution requirement no layer states,
and §1 forbids asserting more than the implementation carries.
Measured band, both ends now load-bearing:
* d >= 17 -> the 1-ULP float tail of a cohort subtraction reaches the JSON
bytes (0.1 - 0.3 publishes as -0.19999999999999998, not -0.2).
* d <= 2 -> the rendered percent moves (2/7 renders 29.0%, not 28.6%).
* d in [3, 16] -> identical to every consumer this system has.
Both proofs are stated WITHOUT reference to the constant's own value — the
exact decimal difference of the two PUBLISHED shares, and a percent computed
from the RAW NOK figures — so they bind the claim rather than the number. A
literal like 0.142857 would only have bound 6 to itself.
The :61 comment justified only the upper end; it now records the measurement
and says plainly that 6 is convention inside the band, not a derived figure.
Mutation-verified: d=2 RED, d=3/4/5/16 GREEN, d=17 RED. Suite 628 -> 631.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MQu2xxwedckjU56byu1aUG
The S5.4 analog: every run/portfolio pass can produce a deterministic value
report — modelled → expert-corrected → realized, goal progress, a quantified
learning effect, cost against value — with no model call, no clock and no new
state. It is a PURE PROJECTION over what is already persisted (K5 outbox pairs,
§4.2 inbox verdicts, K1 ledger), joined on the verdict_id K5 mints.
The honesty rule (§1) sets the shape, not the layout:
- approved -> the claim stands (quantified)
- rejected -> the claim is void, 0 (quantified — an earned zero)
- approved_with_adjustment -> §4.2 carries NO adjusted amount, so the corrected
value is UNQUANTIFIED, never back-filled with the claim
- no verdict -> realized is UNMARKED, never zero-that-reads-as-judged and
never the modelled figure
Partial quantification is counted in the output (2 of 4 …, 2 UNMARKED) rather
than summed into a full-looking total. Learning is measured, not asserted: a
rising approval share is reported only alongside the modelled→corrected gap that
shrank behind it, over cohorts split by run_id order. Cost (USD, a K6 upper
bound) and value (NOK) sit side by side and are never divided — no sourced FX
rate exists here, and a ratio would invent one.
Surfaces: standalone CLI (valuereport) and an opt-in --value-report on run.py,
which requires --outbox and is refused BEFORE any spend without one; the report
is written on both run outcomes and never rewrites the run's exit code (a budget
stop stays a budget stop).
Six seams detach-proven RED: honesty boundary (corrected + realized), gap
arithmetic, projection purity, run-seam wiring, pre-spend fail-fast, both-outcome
reporting. Fixtures are COMMITTED and generated with the real primitives, so the
id-join under test is genuine.
Note on the purity test: it was green-but-dead in its first form. Snapshotting
the committed fixture tree in place let an earlier test's stray write pre-seed
the 'before' snapshot, so the detached write reproduced it byte-for-byte. Every
test now projects from a per-test copy, and a pinned file-set test guards the
committed tree. Found by running the detach proof — which is what §11 is for.
portfolio.py is deliberately NOT wired: run_portfolio persists nothing, so there
is nothing for a projection to read. Its docstring now says that instead of
promising the wiring it did not get.
562 -> 584 tests green; ruff + mypy --strict clean over 27 src files.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MQu2xxwedckjU56byu1aUG
