precision-budget
Skill0 starsChanged 44 days agoMITView on GitHub
This skill should be used when a computation has to be specified rather than just written — "how many digits do I need", "what working precision", "is this bound tight", "why is this result off by a factor of 10^20", "the answer changed when I added precision", "budget the digits", "is 60 digits enough", "prove the precision matters", "knife edge of the expansion". Computes the digit budget from the tribonacci constant, measures whether the budget is actually sufficient by scanning every working precision below it, and shows the same quantity collapsing on a starved budget. Stdlib-only Python 3.10+, no network, no build step.
In this repository9 other files it gives its agents.
- AGENTS.mdAGENTS.md
- claim-ledgerSkill
- elohim-harnessSkill
- elohimSkill
- estimator-biasSkill
- invariant-hunterSkill
- pay-signalSkill
- reproducibilitySkill
- tolerance-proverSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 137
Read every backlog entry before promoting it.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
PRECISION BUDGET
The product of this skill is a digit count, and the evidence that the count matters.
Working precision is the part of a numerical specification that nobody writes down, and the omission is not neutral: a scan of
max over n of |lambda**n - round(lambda**n)| / |alpha|**nover n <= 200 is worth 1.9999748 at the right precision and
3.7e+21 at a starved one. Both are honest outputs of the same code.
Nothing raises, nothing overflows, and the second one looks like a
refutation of Pisot's bound. It is a refutation of the arithmetic.
So the skill does three things, in order:
- it computes the budget.
n_max * (log10(lambda) - log10(|alpha|)) + 30working digits, from the tribonacci constant1.839286755214161132551852564653286600424and the modulus of its conjugate pair. - it measures whether the budget is enough. A formula can be wrong, so
every working precision from 40 to 200 is scanned and the last one that
still breaks the bound is reported. For
n_max = 200the bound holds from 83 digits up and breaks at every precision below it, so the budget of 109 carries 26 digits of margin. That is a claim that can fail, and it is checked rather than assumed. - it shows the flip. The greedy expansion of 1 in base phi, plastic or
tribonacci terminates at some working precisions and not at others. The
exact expansion is a theorem; which precisions find it is an artefact of
rounding. See
references/precision.md.
One measurement is deliberately left out of the ledger, and the reason is
the most useful thing here: the starved maximum is not a reproducible
constant. Give the same scan three more working digits and the number
changes by a factor of several hundred to several thousand, depending on
which route to the root produced it, because the error in the root is
amplified by lambda**n and then divided by |alpha|**n. The budget
figure reproduces digit for digit under a different root finder. Pinning
the starved digits would be pinning noise, so the ledger pins the verdict
that says so instead.
Run the gate
From the repository root:
python3 skills/elohim-harness/scripts/harness_run.py --skill-dir skills/precision-budget| flag | effect |
--json | machine-readable payload on stdout |
--discover | measure the unrefuted claims into backlog.json |
--list-backlog | print measurements not yet promoted |
--promote ID:PATH[:TOL] | pin one backlog measurement as a ledger fact |
Exit 0 when all five gates hold, 1 when one fails, 2 when the skill
or its instrument cannot be located. To run the instrument or either
script on its own, cd nowhere: each resolves its own paths relative to
its own file.
The instrument also honours an override, derived from the directory name the way the contract specifies:
ELOHIM_PRECISION_BUDGET_SCRIPT=/path/to/precision_budget.py \
python3 skills/elohim-harness/scripts/harness_run.py --skill-dir skills/precision-budgetAn override that points at a missing file is an error, exit 2, never a
silent fallback to the bundled copy.
The five gates
pin — the ledger pins this instrument's sha256 and byte count. Holding the instrument beside its ledger fixes only which code runs; the pin is what makes an edit to that code visible instead of silent. Drift prints both hashes and can never resolve to PASS. Expect DRIFT the first time after any change to the instrument: that is the gate working.
ledger — each recorded fact is re-measured against a fresh shard and
reported with its residual. A fact whose path has vanished reports
missing rather than quietly passing. These nine facts started empty:
nothing was written into the ledger that the instrument had not measured
in a run of its own.
traps — six traps in scripts/check_traps.py, each re-deriving its
property from the minimal polynomial with code of its own, then comparing
that against the shard. A trap that imported the instrument would agree
with it by construction. The sharpest of them asks an exact question
instead of a floating-point one: whether 1 is a finite sum of negative
powers of a base is decided by an integer remainder modulo its minimal
polynomial, so a cell the instrument called FINITE either carries the
exact digits or it does not.
hygiene — scripts/check_hygiene.py lints these sources for network
imports and for identifiers a shell filter can rewrite. A gate that
reaches the network is not reproducible, and a gate whose source can be
silently edited is not a gate.
claim binding — elohim-harness/scripts/claim_binding.py pulls every
number out of every claim sentence and requires each one to be a rendering of
a value something pins, part of a formula or a scan window, or declared in
claim_binding_exemptions.json with a written reason. The four gates above
measure the ledger; this one reads the sentence beside the number, which is
where the worst defect this project shipped lived: prose asserting the
opposite of its own pins while every gate reported green, and found by a human
reading the output. A number nothing pins is therefore a failure and not a
warning.
Promote on purpose
--discover re-derives each claim from scratch and writes it to
backlog.json with a contrast: the distance the claim travels. A claim
whose contrast lands below its own tolerance is a positive finding and
has to be promoted, not discarded. abs_alpha.modulus_discrepancy is one:
its contrast is 0.0 against a 1e-15 tolerance, the identity held, and that
is a fact.
--promote ID:PATH[:TOL] then pins one measurement as a ledger fact, and
from then on the harness re-measures it on every run.
Read every backlog entry before promoting it. One is left unpromoted on
purpose: budget_is_load_bearing points at the number of orders the
starved maximum sits above Pisot's bound, and that number depends on the
route to the root. Two independent root finders put it at 21 and at 22.
The blow-up is real and the order of magnitude is not a constant, so it
belongs in the report and not in the ledger. An unpromoted measurement is
not a defect, and a measurement nobody can explain has no business in the
ledger.
Files
| path | role |
instrument/precision_budget.py | the four measurement sections, seals out/shard.json |
ledger.json | the instrument pin and the nine promoted facts |
backlog.json | measured claims, one deliberately left unpromoted |
scripts/discover.py | re-derives the claims, JSON array on stdout |
scripts/check_traps.py | six independent re-derivations, --json |
references/precision.md | the budget derivation, the measured knife-edge table, and what is deliberately not pinned |
out/shard.json | generated; the measurements plus their seal |
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