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reasonsmith — evidence records and reason-deletion certificates for decision systems

tests Python >= 3.11 MIT licence

reasonsmith — prove which legally-owed reasons a system deleted, and from whom

[!TIP] Live on the web: the landing page is at reasonsmith.dev — a scroll-driven flight through the proof graph of the demonstration case — and the self-contained conformance dossier at reasonsmith.dev/report.html. The site lives in its own repo (see #35).

Reasonsmith conformance dossier: headline, key finding and reason audit with the four deleted reasons struck

Prove which legally-owed reasons a system deleted. And from whom.

For anyone who has to answer for an automated decision — the team that built the model, the auditor checking it, the regulator reading the file. reasonsmith checks a decision system against a regulatory duty and states how it knows, instead of returning a tick.

A credit system declined application APP-1042 and stated one reason. Its own inference used five. reasonsmith re-ran that inference, switched each reason off in turn, and named the four the system's answer depended on and its notice never said — and it did not read that from the decision log, because the log records nothing missing.

Two commands, from a bare install, no checkout and no data of your own:

pip install reasonsmith
reasonsmith check --system-module reasonsmith.demo:deployed_credit_system --pack ecoa --system-name TruncatingCreditSystem
CONFORMANCE REPORT
system: TruncatingCreditSystem
declared scope: undeclared
declared domains: consumer-credit
pack: ecoa
headline: 5 requirements · 5 binding: 3 observed, 1 violated, 1 not evaluated

REQUIREMENT FINDINGS:
  [OBSERVED] ecoa_reg_b_1002_9_a_1_timing_of_notice (ECOA / Regulation B (12 CFR 1002.9) 12 CFR 1002.9(a)(1)): satisfied
    requires: artifact_logs_decision_record, artifact_logs_notification_latency_days, artifact_logs_counteroffer_not_accepted
    domain limit: consumer-credit
    summary: Observed over 2 decision(s): temporal monitor for 'always(present(artifact_logs_decision_record) -> ((artifact_logs_notification_latency_days <= 30) or ((artifact_logs_counteroffer_not_accepted >= 0.5) and (artifact_logs_notification_latency_days <= 90))))' satisfied at every decision step.
  [OBSERVED] ecoa_reg_b_1002_9_a_2_written_statement (ECOA / Regulation B (12 CFR 1002.9) 12 CFR 1002.9(a)(2)): satisfied
    requires: artifact_logs_decision_record, provenance_model_version
    domain limit: consumer-credit
    summary: Observed over 2 decision(s): temporal monitor for 'always(present(artifact_logs_decision_record) and present(provenance_model_version) and (present(artifact_logs_reason_explanation) or present(artifact_logs_right_to_reasons_disclosure)))' satisfied at every decision step.
  [OBSERVED] ecoa_reg_b_1002_9_b_2_specific_reasons (ECOA / Regulation B (12 CFR 1002.9) 12 CFR 1002.9(b)(2)): satisfied
    requires: artifact_logs_reason_explanation, provenance_model_version, scope_statements_local_vs_global
    domain limit: consumer-credit
    summary: Observed over 2 decision(s): state monitor for 'present(artifact_logs_reason_explanation) -> ( present(provenance_model_version) and present(scope_statements_local_vs_global) and not contains(artifact_logs_reason_explanation, "internal standards") and not contains(artifact_logs_reason_explanation, "internal policies") and not contains(artifact_logs_reason_explanation, "failed to achieve a qualifying score"))' satisfied at every decision step.
  [PROBED] ecoa_reg_b_1002_9_b_2_principal_reasons_complete (ECOA / Regulation B (12 CFR 1002.9) 12 CFR 1002.9(b)(2)): violated
    requires: artifact_logs_reason_explanation, artifact_logs_deleted_reason_count
    domain limit: consumer-credit
    summary: Violated on 1 of 2 certified decision(s): the stated reasons are not all the reasons. On decision #1 exact inference found 5 reason(s) and the deletion probe showed the system's answer does not depend on 4 of them — C05 — Insufficient number of credit references provided; C03 — Delinquent past or present credit obligations; C04 — Too many recent inquiries on credit bureau report; C02 — Length of time credit has been established is too short. Attribution: The deleted reasons are exactly the 4 lowest-scoring of the 5, and the engine kept the top 1. This is the signature of top-k proof truncation at k=1: top-k works by discarding proofs, so the dropped reasons are lost by configuration, not by error. The missing probability mass is 0.225799. Measured against the inference artefact the system exposed, not read from its decision log.
    offending record: decision APP-1042 (step 1)
    probe budget: 8 input(s) replayed, seed none — the proof enumeration and the deletion probes are deterministic, input space: decisions certified (2 values), reasons switched off (6 values). Strategy: for each decision the system exposed an inference artefact for, its reasons are enumerated exactly by bounded proof enumeration over the ground program and scored by exact weighted model counting; each reason holding a fact no other reason uses is then switched off alone and the system's own engine re-run on the perturbed interpretation. A reason whose deletion moves exact inference but leaves the engine unchanged is a reason the engine's answer does not depend on, and is counted here
  [NOT EVALUATED] ecoa_reg_b_1002_4_a_no_disparate_treatment (ECOA / Regulation B (12 CFR 1002.4) 12 CFR 1002.4(a)): inconclusive
    requires: artifact_logs_decision_record, applicant_prohibited_basis
    domain limit: consumer-credit
    summary: Not evaluated: the system exposes no decide(), so there is no twin decision to run. A counterfactual is what the system would have decided, and a decision log records only what it did — no trace, however long, establishes one. Limit of this duty: it is invariance under one named variable holding all others fixed, so it is a property of treatment and says nothing about effects. A proxy is invisible to it — a rule set that never reads the protected variable and decides by postcode is satisfied here — and a disparate impact is not a thing it can find. It also reaches exactly one variable: a system answerable on several prohibited bases is answered here about the one this duty names.

LIMITS OF THIS REPORT
  This report is not a compliance guarantee and is not legal advice. It assesses system capability information and trace evidence against formal specifications. Whether these findings discharge legal duties remains a determination this tool does not make and cannot make. A requirement reported without a strength was not evaluated or is not applicable, and no verdict on it should be read from this report. Recital and guidance items inform how statutory duties are interpreted but create no obligation of their own; interpretive requirements are evaluated and reported separately, and are never folded into the binding headline counts. A requirement reported not applicable was excluded on one of two independent gates. Either no regulatory class was declared for the system at all, or the class that was declared is not the one the requirement is limited to; or no decision domain was declared for the system at all, or none of the domains that were declared is one the requirement is about. This tool infers neither the class nor the domain, so an undeclared system is neither placed in scope nor cleared of the duty: read the declared scope and domain lines before reading a not-applicable result. The decision-domain vocabulary is written by the pack author and by no regulation, and a duty declaring no domain reaches every system it is run against.

Form completeness does not imply reason fidelity. 12 CFR 1002.9(b)(2) asks two things of an adverse-action notice, and this repository ships them as two duties. ..._specific_reasons reads the notice's form: a statement of reasons is there, and it is none of the wordings the clause itself calls insufficient. ..._principal_reasons_complete reads its content: are the reasons stated all the reasons the decision's own inference used? On APP-1042 the first comes back satisfied and the second comes back violated — which is the finding, not an inconsistency. Checking form alone launders that gap into a document that reads as authoritative: on this same decision the Table 7 evidence record is COMPLETE, and it is the reason-deletion certificate beneath it that reads FAIL. That record, that certificate and the four struck reasons are in docs/example-output.md.

The same violation ships as an example you can run without the CLI, alongside three that pass:

python -m reasonsmith.examples.truncating_credit_system

Before you go further, the four things this tool cannot do — it takes a system's word about what it is, three quarters of the shipped duties are presence checks, a rung is not a grade, and the strongest results need a system that exposes its inference: docs/what-this-does-not-do.md. Every claim there cites the committed document that already states it, with the numbers.

One run, five readers

The block above is one rendering of that run, not the only one. --audience renders the same run for a named reader — five ship: developer, deployer, auditor, regulator, affected-individual — and it changes what is shown, never what is claimed. Nothing is recomputed per reader: every part of every view is a part of the single report the run already produced. No reader is shown a verdict another reader is not shown, no reader loses the limits section, and dropping the flag renders the full report — which is the auditor's view, by identity, so the transcript above is already one of the five.

Here is that run for a regulator. Same five verdicts, same strengths, different content: every requires: line is gone, and the domain limit: line that decides whether the duty reaches this system at all stays. A regulator's question is how far a claim reaches, so the probe budget stays too; the internal signal names and — on a run that produces them — the trace witnesses holding real applicants' records do not.

reasonsmith check --system-module reasonsmith.demo:deployed_credit_system --pack ecoa --system-name TruncatingCreditSystem --audience regulator
CONFORMANCE REPORT
system: TruncatingCreditSystem
declared scope: undeclared
declared domains: consumer-credit
pack: ecoa
headline: 5 requirements · 5 binding: 3 observed, 1 violated, 1 not evaluated

REQUIREMENT FINDINGS:
  [OBSERVED] ecoa_reg_b_1002_9_a_1_timing_of_notice (ECOA / Regulation B (12 CFR 1002.9) 12 CFR 1002.9(a)(1)): satisfied
    domain limit: consumer-credit
    summary: Observed over 2 decision(s): temporal monitor for 'always(present(artifact_logs_decision_record) -> ((artifact_logs_notification_latency_days <= 30) or ((artifact_logs_counteroffer_not_accepted >= 0.5) and (artifact_logs_notification_latency_days <= 90))))' satisfied at every decision step.
  [OBSERVED] ecoa_reg_b_1002_9_a_2_written_statement (ECOA / Regulation B (12 CFR 1002.9) 12 CFR 1002.9(a)(2)): satisfied
    domain limit: consumer-credit
    summary: Observed over 2 decision(s): temporal monitor for 'always(present(artifact_logs_decision_record) and present(provenance_model_version) and (present(artifact_logs_reason_explanation) or present(artifact_logs_right_to_reasons_disclosure)))' satisfied at every decision step.
  [OBSERVED] ecoa_reg_b_1002_9_b_2_specific_reasons (ECOA / Regulation B (12 CFR 1002.9) 12 CFR 1002.9(b)(2)): satisfied
    domain limit: consumer-credit
    summary: Observed over 2 decision(s): state monitor for 'present(artifact_logs_reason_explanation) -> ( present(provenance_model_version) and present(scope_statements_local_vs_global) and not contains(artifact_logs_reason_explanation, "internal standards") and not contains(artifact_logs_reason_explanation, "internal policies") and not contains(artifact_logs_reason_explanation, "failed to achieve a qualifying score"))' satisfied at every decision step.
  [PROBED] ecoa_reg_b_1002_9_b_2_principal_reasons_complete (ECOA / Regulation B (12 CFR 1002.9) 12 CFR 1002.9(b)(2)): violated
    domain limit: consumer-credit
    summary: Violated on 1 of 2 certified decision(s): the stated reasons are not all the reasons. On decision #1 exact inference found 5 reason(s) and the deletion probe showed the system's answer does not depend on 4 of them — C05 — Insufficient number of credit references provided; C03 — Delinquent past or present credit obligations; C04 — Too many recent inquiries on credit bureau report; C02 — Length of time credit has been established is too short. Attribution: The deleted reasons are exactly the 4 lowest-scoring of the 5, and the engine kept the top 1. This is the signature of top-k proof truncation at k=1: top-k works by discarding proofs, so the dropped reasons are lost by configuration, not by error. The missing probability mass is 0.225799. Measured against the inference artefact the system exposed, not read from its decision log.
    probe budget: 8 input(s) replayed, seed none — the proof enumeration and the deletion probes are deterministic, input space: decisions certified (2 values), reasons switched off (6 values). Strategy: for each decision the system exposed an inference artefact for, its reasons are enumerated exactly by bounded proof enumeration over the ground program and scored by exact weighted model counting; each reason holding a fact no other reason uses is then switched off alone and the system's own engine re-run on the perturbed interpretation. A reason whose deletion moves exact inference but leaves the engine unchanged is a reason the engine's answer does not depend on, and is counted here
  [NOT EVALUATED] ecoa_reg_b_1002_4_a_no_disparate_treatment (ECOA / Regulation B (12 CFR 1002.4) 12 CFR 1002.4(a)): inconclusive
    domain limit: consumer-credit
    summary: Not evaluated: the system exposes no decide(), so there is no twin decision to run. A counterfactual is what the system would have decided, and a decision log records only what it did — no trace, however long, establishes one. Limit of this duty: it is invariance under one named variable holding all others fixed, so it is a property of treatment and says nothing about effects. A proxy is invisible to it — a rule set that never reads the protected variable and decides by postcode is satisfied here — and a disparate impact is not a thing it can find. It also reaches exactly one variable: a system answerable on several prohibited bases is answered here about the one this duty names.

LIMITS OF THIS REPORT
  This report is not a compliance guarantee and is not legal advice. It assesses system capability information and trace evidence against formal specifications. Whether these findings discharge legal duties remains a determination this tool does not make and cannot make. A requirement reported without a strength was not evaluated or is not applicable, and no verdict on it should be read from this report. Recital and guidance items inform how statutory duties are interpreted but create no obligation of their own; interpretive requirements are evaluated and reported separately, and are never folded into the binding headline counts. A requirement reported not applicable was excluded on one of two independent gates. Either no regulatory class was declared for the system at all, or the class that was declared is not the one the requirement is limited to; or no decision domain was declared for the system at all, or none of the domains that were declared is one the requirement is about. This tool infers neither the class nor the domain, so an undeclared system is neither placed in scope nor cleared of the duty: read the declared scope and domain lines before reading a not-applicable result. The decision-domain vocabulary is written by the pack author and by no regulation, and a duty declaring no domain reaches every system it is run against.

And the same run for the person the decision was about — the narrowest artefact this tool renders, and the only one that is derived rather than narrowed. It carries no system internals at all: no signal names, no probe budget, no counterexamples, and no strength vocabulary, because being told a duty is probed hands a person this tool's evidence model instead of an answer. What it carries instead is the part of this same run no other view says out loud — the decision the system recorded and the reason it stated, in its own words, and the reasons the certificate engine measured it used and did not state.

reasonsmith check --system-module reasonsmith.demo:deployed_credit_system --pack ecoa --system-name TruncatingCreditSystem --audience affected-individual
CONFORMANCE REPORT
system: TruncatingCreditSystem
pack: ecoa

WHAT THE SYSTEM RECORDED ABOUT THE 2 DECISIONS IT LOGGED
    the decision it recorded: "adverse action on APP-1043"
    the reason it stated: "C01 — Income insufficient for amount of credit requested"
    the decision it recorded: "adverse action on APP-1042"
    the reason it stated: "C01 — Income insufficient for amount of credit requested"

WHETHER THOSE WERE ALL THE REASONS
    4 further reason(s) the system's own answer depended on were not stated. Measured by re-running its inference, not inferred from its log:
    "C05 — Insufficient number of credit references provided"
    "C03 — Delinquent past or present credit obligations"
    "C04 — Too many recent inquiries on credit bureau report"
    "C02 — Length of time credit has been established is too short"

WHAT THIS REPORT COULD NOT CHECK
    1 duty: no check in this report could settle it, so it was left open rather than answered.

REQUIREMENT FINDINGS:
  ecoa_reg_b_1002_9_a_1_timing_of_notice (ECOA / Regulation B (12 CFR 1002.9) 12 CFR 1002.9(a)(1)): satisfied
  ecoa_reg_b_1002_9_a_2_written_statement (ECOA / Regulation B (12 CFR 1002.9) 12 CFR 1002.9(a)(2)): satisfied
  ecoa_reg_b_1002_9_b_2_specific_reasons (ECOA / Regulation B (12 CFR 1002.9) 12 CFR 1002.9(b)(2)): satisfied
  ecoa_reg_b_1002_9_b_2_principal_reasons_complete (ECOA / Regulation B (12 CFR 1002.9) 12 CFR 1002.9(b)(2)): violated
  ecoa_reg_b_1002_4_a_no_disparate_treatment (ECOA / Regulation B (12 CFR 1002.4) 12 CFR 1002.4(a)): inconclusive

LIMITS OF THIS REPORT
  This report is not a compliance guarantee and is not legal advice. It assesses system capability information and trace evidence against formal specifications. Whether these findings discharge legal duties remains a determination this tool does not make and cannot make. A requirement reported without a strength was not evaluated or is not applicable, and no verdict on it should be read from this report. Recital and guidance items inform how statutory duties are interpreted but create no obligation of their own; interpretive requirements are evaluated and reported separately, and are never folded into the binding headline counts. A requirement reported not applicable was excluded on one of two independent gates. Either no regulatory class was declared for the system at all, or the class that was declared is not the one the requirement is limited to; or no decision domain was declared for the system at all, or none of the domains that were declared is one the requirement is about. This tool infers neither the class nor the domain, so an undeclared system is neither placed in scope nor cleared of the duty: read the declared scope and domain lines before reading a not-applicable result. The decision-domain vocabulary is written by the pack author and by no regulation, and a duty declaring no domain reaches every system it is run against.

What that view is still not: an adverse-action notice. Everything above is the system's own words and the engines' own measurements, quoted — the log said this, the certificate found these four reasons went unstated — and not one sentence of it paraphrases the statute, explains the decision, or advises. A conformance report does not hold the adverse-action statement a creditor owes a person and this projection will not write one. Where a run has less to quote it says so rather than going quiet: a run that read no decision record says that, and a run where nothing measured whether the stated reasons were complete says that, because silence there reads as a clean result to the reader least equipped to know otherwise. The full row-by-row table of what each of the five readers is shown — authored here, not derived from the law, so it can be argued with — is in docs/semantics.md §7.

--audience projects the text and HTML renderings only. --json stays the complete machine record, so a pipeline never loses fields to a display flag — and so --audience affected-individual --json is not a redaction. Redaction is a security property; this is a presentation one. The decision accounts the lay view quotes are the one thing not in it, for the opposite reason: the JSON is the findings record, and what the system logged is an input the run read rather than a finding it made.

Any model in: one duty, three systems, three rungs

The run above held one system fixed and varied the property, so it answers what a property actually says. This section does the opposite — one duty, three systems — so it answers how far a claim reaches. Two different questions about the same tool; neither answers the other, which is why both are on this page.

Neural, probabilistic or symbolic — a system is fed in by writing an adapter that says what it exposes, and what kind of decision it makes. These three, all checked against the same binding duty (ECOA / Reg B 12 CFR 1002.9(b)(2), "the statement of reasons ... must be specific"), come back at three different rungs:

system what it exposes rung reached
neural risk network, served behind an inference API decisions() — an exported decision log, nothing else observed
probabilistic log-odds scorer, in-process decisions() + decide(case) replay probed, carrying its search budget
symbolic underwriting rule set decisions() + logic() proved, over every input the constraints admit

All three also declare system_domains = ("consumer-credit",), which is what puts them inside a duty about adverse-action reasons at all: 12 CFR 1002.9 is about consumer-credit decisions, and a system that has declared no decision domain is reported not applicable rather than judged. Raising a rung means changing the system; declaring a domain it is not in would be a different error entirely.

These three systems ship inside the package, so the commands below run against a pip install reasonsmith with no checkout and no data of your own:

for s in neural_scorer probabilistic_scorer symbolic_rules; do python -m reasonsmith.examples.$s; done

The CLI reaches the same three systems against a whole pack, no Python needed — --system-module imports the named module, which executes it, and takes the attribute after the colon as the system under test (the module:attribute spelling pytest's -p and gunicorn's application path use):

reasonsmith check --system-module reasonsmith.examples.symbolic_rules:system_under_test --pack ecoa

All three verdicts here are satisfied — the shipped example that comes back violated is the truncating credit system of the first section — and the rung is what separates these three: how far each claim reaches — three logged decisions, 200 replayed inputs, or every input the declared constraints admit. The neural system cannot reach probed or proved as built, and no adapter can change that; a test pins that ceiling. Full walkthrough, with the three transcripts and why this duty was chosen over a recital: docs/three-systems.md.

A further system — a language model prompted to write the notice — adds no rung: a model you can call sits at probed, where the probabilistic scorer already sits. It is worth a document of its own for the other axis, which duties can be answered about a system at all. Run against the whole ecoa pack it comes back observed on the notice's timing and contents, probed on 12 CFR 1002.9(b)(2)'s specific-reasons duty, and unattainable on the other half of that same clause, naming the signal it lacks — because reason fidelity is measured from an inference artefact and a decoder has none. reasonsmith refuses that duty rather than passing the system on the easier one beside it: docs/language-model.md.

The state of the art, the gap, and what this adds

Where compliance tooling stands. Checking an automated decision system against a regulatory duty is, in practice, checking a document. Model cards, datasheets, audit-log schemas, the EU AI Act's own Article 12 record-keeping duty: each names artefacts the system must produce, and a checker reads what was produced and reports which required fields are filled. That is a real check and it catches real gaps — a missing reason field is a missing reason field.

The gap. Existing compliance tools check whether a log has the required fields. None of them states what strength of evidence stands behind the verdict. A checker reading a decision log can speak only about the decisions in that log; a checker reasoning over a system's decision rules can speak about every input those rules admit. Both report the same word. The reader of the report cannot tell which one happened, so a claim about three logged decisions and a claim about an unbounded input space arrive indistinguishable — and the weaker of the two is the one that is easy to produce.

What reasonsmith adds. Every verdict carries the method that reached it, on a strict lattice — unattainable < observed < probed < proved — and a result no engine could establish carries no strength at all rather than a satisfied verdict. Which rung a duty reaches is a fact about the system under test, not about which word a pack author typed: the same property is read off a trace, searched by replay, or proved by a solver depending only on what the system exposes. RequirementResult refuses to be constructed claiming more than it has, so the bound travels into every rendering instead of being a convention some renderer might drop. The three-systems table above is that claim under test — one duty, three systems, three different rungs — rather than an illustration of it.

What this does not claim. A rung is not a compliance grade and not a confidence score: it ranks how a conclusion was reached, never what it was reached about, so a proved verdict over logic unrelated to the deployed system is worth less than an observed verdict over a year of production decisions, and the lattice cannot see that. Nothing here determines whether a legal duty is discharged. The full statement of what each rung does and does not mean, one engine at a time, is docs/semantics.md.

The two concrete questions

Given a decision, the symbolic artifact behind it, and an applicable duty, reasonsmith answers:

  1. Is the evidence record complete? Does it carry every field the duty's formal specification requires?
  2. Did the explanation engine keep the reasons it was supposed to give? Or did it drop some on the way out?

The first is evaluated against the formal specification and reported with its strength. The second compares actual engine behavior against ground-truth exact inference: where the applicable requirement identifies reasons the statute obliges, its paired reason-deletion certificate shows which of them the engine dropped. Where the system exposes the inference artefact behind a decision, that certificate is itself an engine, so the second question is answered as a requirement verdict rather than alongside one.

What a verdict is worth

Every evaluated result records its evidence strength, on one lattice:

  • unattainable — on a declared basis, signals the duty needs are outside the system's declared capability set; on a trace basis, no supplied record carries them, which does not establish that the system cannot emit them. Computed without executing the system; the missing signals are named.
  • observed — read off the decision trace supplied; it claims nothing about decisions outside it.
  • probed — a bounded search, never a proof: the engine perturbs the decisions the system has already made, replays each generated input through the system itself, reports any counterexample it finds within the budget and otherwise reports that none was found, naming exactly what was searched.
  • proved — a solver result: the decision logic the system exposes is checked over every input the declared constraints admit, and a counterexample is executed before it is reported as a violation.

Combining zero verdicts is inconclusive, never vacuously satisfied. A requirement no engine here can evaluate is reported with no strength, rather than judged by a weaker check. What each verdict means — and does not mean — is stated one engine at a time in docs/semantics.md; every soundness claim there names the test that fails if the claim becomes false.

How each shipped requirement got from a clause of law to a formula — and, in a fourth column, what that refinement deliberately did not capture — is recorded in docs/refinement.md, one row per requirement across all five packs.

Can it use a different formalism? Engines and packs install

Seven engines ship here, but the set is not closed. An engine is discovered through the reasonsmith.engines entry-point group and a pack through reasonsmith.packs, so a Prolog, ASP or other-solver engine — and a regulation pack this repository does not carry — ships as your pip package and joins the run the moment it is installed, with no pull request here. The property language does not change: a plug-in engine is handed the same requirement in the same language the built-ins get. What opens is which engine may discharge a duty, and nothing else. A plug-in cannot report above the max_strength it declares, one that raises, will not import or returns the wrong type is reported not evaluated rather than satisfied, and every plug-in result names its plug-in. There is no wall clock, so a plug-in that hangs hangs the run — and nothing here audits a plug-in, so a proved from an engine this repository never saw is worth the installer's trust in that package and no more. What to supply, and what that trust does and does not buy: docs/authoring-engines.md.

Automated Conformance Checking

A decision log is the commonest system and the weakest: it exposes no inference artefact, so the same pack that reported the adequacy duty violated above reports it unattainable here, naming the signal nothing in the log could supply — never returning it to the presence check. The committed sample log ships with the package, and python -m reasonsmith.examples prints the directory it was installed into, so this runs against the same pack with no data of your own:

reasonsmith check --system "$(python -m reasonsmith.examples)/sample_decisions.jsonl" --pack ecoa --system-name CreditScoringPipeline --system-domain consumer-credit
CONFORMANCE REPORT
system: CreditScoringPipeline
declared scope: undeclared
declared domains: consumer-credit
pack: ecoa
headline: 5 requirements · 5 binding: 3 observed, 1 not evaluated, 1 unattainable

REQUIREMENT FINDINGS:
  [OBSERVED] ecoa_reg_b_1002_9_a_1_timing_of_notice (ECOA / Regulation B (12 CFR 1002.9) 12 CFR 1002.9(a)(1)): satisfied
    requires: artifact_logs_decision_record, artifact_logs_notification_latency_days, artifact_logs_counteroffer_not_accepted
    domain limit: consumer-credit
    summary: Observed over 3 decision(s): temporal monitor for 'always(present(artifact_logs_decision_record) -> ((artifact_logs_notification_latency_days <= 30) or ((artifact_logs_counteroffer_not_accepted >= 0.5) and (artifact_logs_notification_latency_days <= 90))))' satisfied at every decision step.
  [OBSERVED] ecoa_reg_b_1002_9_a_2_written_statement (ECOA / Regulation B (12 CFR 1002.9) 12 CFR 1002.9(a)(2)): satisfied
    requires: artifact_logs_decision_record, provenance_model_version
    domain limit: consumer-credit
    summary: Observed over 3 decision(s): temporal monitor for 'always(present(artifact_logs_decision_record) and present(provenance_model_version) and (present(artifact_logs_reason_explanation) or present(artifact_logs_right_to_reasons_disclosure)))' satisfied at every decision step.
  [OBSERVED] ecoa_reg_b_1002_9_b_2_specific_reasons (ECOA / Regulation B (12 CFR 1002.9) 12 CFR 1002.9(b)(2)): satisfied
    requires: artifact_logs_reason_explanation, provenance_model_version, scope_statements_local_vs_global
    domain limit: consumer-credit
    summary: Observed over 3 decision(s): state monitor for 'present(artifact_logs_reason_explanation) -> ( present(provenance_model_version) and present(scope_statements_local_vs_global) and not contains(artifact_logs_reason_explanation, "internal standards") and not contains(artifact_logs_reason_explanation, "internal policies") and not contains(artifact_logs_reason_explanation, "failed to achieve a qualifying score"))' satisfied at every decision step.
  [UNATTAINABLE] ecoa_reg_b_1002_9_b_2_principal_reasons_complete (ECOA / Regulation B (12 CFR 1002.9) 12 CFR 1002.9(b)(2)): inconclusive
    requires: artifact_logs_reason_explanation, artifact_logs_deleted_reason_count
    domain limit: consumer-credit
    MISSING SIGNALS: artifact_logs_deleted_reason_count
    summary: Unattainable on the evidence supplied: no record in the supplied decision trace carries a value for artifact_logs_deleted_reason_count, and the system declared no capabilities, so nothing here can discharge this requirement. Read from that trace alone; a longer trace could show the system emitting these signals.
  [NOT EVALUATED] ecoa_reg_b_1002_4_a_no_disparate_treatment (ECOA / Regulation B (12 CFR 1002.4) 12 CFR 1002.4(a)): inconclusive
    requires: artifact_logs_decision_record, applicant_prohibited_basis
    domain limit: consumer-credit
    summary: Not evaluated: the system exposes no decide(), so there is no twin decision to run. A counterfactual is what the system would have decided, and a decision log records only what it did — no trace, however long, establishes one. Limit of this duty: it is invariance under one named variable holding all others fixed, so it is a property of treatment and says nothing about effects. A proxy is invisible to it — a rule set that never reads the protected variable and decides by postcode is satisfied here — and a disparate impact is not a thing it can find. It also reaches exactly one variable: a system answerable on several prohibited bases is answered here about the one this duty names.

LIMITS OF THIS REPORT
  This report is not a compliance guarantee and is not legal advice. It assesses system capability information and trace evidence against formal specifications. Whether these findings discharge legal duties remains a determination this tool does not make and cannot make. A requirement reported without a strength was not evaluated or is not applicable, and no verdict on it should be read from this report. Recital and guidance items inform how statutory duties are interpreted but create no obligation of their own; interpretive requirements are evaluated and reported separately, and are never folded into the binding headline counts. A requirement reported not applicable was excluded on one of two independent gates. Either no regulatory class was declared for the system at all, or the class that was declared is not the one the requirement is limited to; or no decision domain was declared for the system at all, or none of the domains that were declared is one the requirement is about. This tool infers neither the class nor the domain, so an undeclared system is neither placed in scope nor cleared of the duty: read the declared scope and domain lines before reading a not-applicable result. The decision-domain vocabulary is written by the pack author and by no regulation, and a duty declaring no domain reaches every system it is run against.

observed is the weakest rung of the strength lattice that can still say a property held: it is read off the trace supplied and claims nothing about decisions outside it. --system-domain consumer-credit is what puts this log inside 12 CFR 1002.9 at all: those duties are about consumer-credit decisions, and a system that declares no decision domain has them reported not applicable rather than checked. The same log checked against the Table 7 pack still exits 0, because nothing there is a breach: the GDPR Art. 22 and ECOA rows come back observed, the NIST row comes back unattainable with its missing signals named, the FDA GMLP row comes back not applicable because it is about healthcare decisions, and the two EU AI Act rows come back not applicable against an undeclared regulatory scope — declaring it with --system-scope high-risk is what brings them into scope, and that is the run behind the dossier at reasonsmith.dev/report.html. See docs/example-output.md for that run and for the full 905-line demo transcript, both stdout pasted unedited.

Quick Start

  1. Install the published package. This puts the reasonsmith command on your PATH, with python -m reasonsmith.cli staying available:
pip install reasonsmith
  1. Run the shipped demonstration:
python -m reasonsmith.demo

The demonstration runs on frozen synthetic data included in the package. It needs no input file or source checkout and prints the complete demonstration, including the NOT PRODUCED reasoning and LIMITS sections.

  1. Audit your own decision log against a regulation pack:
reasonsmith check --system /path/to/your-decisions.jsonl --pack gdpr --html report.html

check runs one of the five shipped packs (Table 7, EU AI Act (Art. 12 & 13), GPAI (EU AI Act Art. 53 & 55), GDPR, ECOA/Reg B) against your JSONL decision log, printing the report as text, JSON (--json), or a self-contained HTML report (--html FILE). It exits 2 when a requirement is violated, 1 on a usage or input error, and 0 otherwise.

A decision log exposes neither decide() nor logic(), so a --system run cannot rise above observed. To check the system itself, name an adapter instead:

reasonsmith check --system-module your_package.audit:system_under_test --pack gdpr

--system-module imports the named module, which executes it, and takes the attribute after the colon — a SystemUnderTest or a zero-argument factory returning one — as the system under test. The module is searched from the current directory. It refuses --system and --capabilities, which name a different system and speak for a log's adapter respectively. Three worked examples: docs/three-systems.md.

Contributors and developers install from source instead, running the full verification suite and demonstration from the checkout:

git clone https://github.com/eduardstan/reasonsmith.git
cd reasonsmith
python3 -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
ruff check .
pytest
python -m reasonsmith.demo
reasonsmith check --system src/reasonsmith/examples/sample_decisions.jsonl --pack ecoa --system-domain consumer-credit

Every command in the source block runs from a fresh clone in that order; the ecoa run above exits 0.

Note: This source install is the one CI itself runs (.github/workflows/ci.yml). Full empirical environment measurements and torch test counts are documented in RESULTS.md.

Where the Duties Come From

The duty-to-artifact mapping is Table 7 of Symbols and Neurons: A Review of Symbolic XAI in Deep Learning (Stan, Sciavicco & Napoletano, JAIR 2026, p. 36:22), reviewing 273 primary studies across five regulatory frameworks: EU AI Act, GDPR, ECOA/Reg B, FDA GMLP, and NIST AI RMF.

Table 7 is transcribed verbatim into src/reasonsmith/table7.toml. That file is data, not code: every duty records its row number, and every machine key sits next to the exact cell text it stands for. traceability_report() prints the table side by side. Where a design decision and Table 7 disagree, Table 7 wins. Statutory texts are backed by retrieval records in docs/legal-sources.md.

What Is in the Box

Package Architecture

File / Module Description
src/reasonsmith/__init__.py The package's public surface and __version__, which reasonsmith --version prints
src/reasonsmith/table7.toml The six Table 7 duties transcribed verbatim, with row-level traceability
src/reasonsmith/evidence.py Minimal evidence record emitter and missing field reporter
src/reasonsmith/certificate.py Reason-deletion certificates against exact inference oracle (nesyarena)
src/reasonsmith/conformance.py Table 19 checks, including stratified per-group evaluations
src/reasonsmith/demo.py End-to-end demonstration of all six Table 7 duties (EU AI Act Art. 13 and Art. 12, GDPR Art. 22 clinical, ECOA/Reg B credit, FDA GMLP SaMD, NIST AI RMF continuous monitoring)
src/reasonsmith/verdict.py Core lattice: evidence strength lattice (unattainable < observed < probed < proved) and verdict vocabulary
src/reasonsmith/spec.py Core requirement loader & specification structures from packs/*.toml
src/reasonsmith/sut.py System-under-test protocol — declared capabilities, decision trace, optional replay hook, and exposed logic
src/reasonsmith/report.py Conformance report skeleton, headline builder, static unattainable analysis, the engine ladder, and both applicability gates
src/reasonsmith/render.py The text and self-contained-HTML renderings of a report, and the five audience projections (AUDIENCES) --audience selects between; ConformanceReport.render_text/render_html delegate here
src/reasonsmith/plugins.py Discovery of engines and packs installed as separate pip packages, through the reasonsmith.engines and reasonsmith.packs entry-point groups (docs/authoring-engines.md)
src/reasonsmith/rulelang.py The whitelisted mini-language rule and specification text is parsed and executed in, shared by the rule adapter and the proved engine
src/reasonsmith/adapters/ SUT protocol adapters for JSONL decision logs, Python callables, and rule-based systems that expose their decision logic
src/reasonsmith/engines/ Verification engines: record completeness check, observed rtamt monitor over a trace (temporal formulas and per-record state properties), probed perturb-and-replay search, proved Z3 solver, temporal — the same solver, over an always(f) reduced to a property of one decision — and counterfactual, the one engine over a pair of executions: Z3 self-composition at proved, paired replay at probed, and no trace rung
src/reasonsmith/examples/ The five runnable example systems — including the one that comes back violated — and sample_decisions.jsonl, shipped in the wheel so every documented command runs after pip install; python -m reasonsmith.examples prints the directory they installed into
src/reasonsmith/cli.py Command-line interface (reasonsmith / python -m reasonsmith.cli): check --system /path/to/your-decisions.jsonl --pack gdpr --capabilities /path/to/capabilities.txt and validate-pack gdpr
src/reasonsmith/drift.py Statute drift check (python -m reasonsmith.drift): re-fetches the official legal sources and re-verifies every pack quote, reporting match / differ / could-not-verify without ever editing a pack
src/reasonsmith/packs/table7.toml Table 7 rows restated as a formal requirement pack
src/reasonsmith/packs/{eu_ai_act,gpai,gdpr,ecoa}.toml Statutory requirement packs with verbatim quotes from docs/legal-sources.md

Core Components

  • The Emitter (evidence.py): emit(duty_id, decision_id, fields) returns a record that is either COMPLETE or INCOMPLETE. An INCOMPLETE record explicitly names the fields it lacks. Nothing is defaulted, inferred, or silently dropped. Keys outside the duty's Table 7 row are rejected, and non-Table 7 data is isolated in attachments.

  • The Reason-Deletion Certificate (certificate.py): Compares the reasons an engine actually used against exact inference ground truth (enumerated via WMC in nesyarena). Using deletion probes, it tests whether disabling isolated facts changes engine output. Two independent checks must pass: the deletion probe (every reason live) and the value check against the exact oracle. Reasons that cannot be probed in isolation are reported as uncertified (INCONCLUSIVE). It is reachable from a conformance run: the Certificate Engine (engines/certificate.py) runs it over the inference artefact a system exposes through the optional artifact(decision) hook, measures the deleted-reason count itself rather than reading one the system logged, and discharges ecoa_reg_b_1002_9_b_2_principal_reasons_complete at strength probed — a system exposing no artefact is reported unattainable on that duty and never downgraded to the presence check on the reason field. See docs/semantics.md §3, certificate.

  • The Conformance Core (verdict.py, report.py): Every evaluated result records its evidence strength: unattainable < observed < probed < proved. unattainable is a set difference over SUT capabilities computed without running the system: with declared capabilities it describes the system, while with trace-derived capabilities it describes only the supplied records; either way, the missing signals are named. observed evaluates passive decision traces. probed actively replays perturbed inputs. proved is a solver result. A requirement no engine here can evaluate is reported as not evaluated — no strength and no satisfied-or-violated conclusion — rather than judged by a weaker check. Combining zero verdicts is inconclusive, never vacuously satisfied. Every requirement's spec is a formula in one property language (rulelang.py), and formalism names which fragment it belongs to: record (a conjunction of present(signal) atoms), temporal (a formula using a temporal operator), logical (any other property of one decision record), and counterfactual (the one relational atom, a property of a pair of executions, which is the whole of a spec or no part of one). The fragment says what the property is; what discharges it is a fact about the system, not about the pack — the same presence property is observed against a trace, probed against a system exposing decide(), and proved against one exposing logic(). See docs/semantics.md §3.5.

  • The Proved Engine (engines/proved.py): logical requirements are discharged by Z3 against the decision logic a system exposes through sut.logic() — its variables, its rules, the constraints its inputs are known to obey, and which of those variables it computes. That last declaration is what separates an input the decision situation supplies from an output the system produces, and a property naming something in neither — a name the system has no notion of — is refused a proof rather than answered from a constant the solver invented. Rules are encoded in static single assignment form, so a rule that reassigns a name means what it means when executed. Three things are refused rather than reported: logic or a property using a construct the encoding does not model, a solver result of unknown or a timeout, and premises no input can satisfy — an over-constrained model makes unsat prove every property alike, so it counts as no evidence, not as proof. When the solver finds a counterexample, that input is executed before anything is reported: VIOLATED at strength proved is only claimed once the violation reproduces, and the evidence summary names what it reproduced against, since a system exposing only logic() can be replayed only through its declared logic and not through itself. The GDPR pack ships the first logical requirement proved against real statute: gdpr_art22_1_no_prohibited_decision_for_any_input asks Z3 whether the exposed rules admit any input on which a decision is solely automated and significantly affecting while no Article 22(2) basis applies and the Article 22(3) route to human intervention is closed. That duty is universal, so a record check over a supplied trace cannot express it; a proved verdict here is a statement about the exposed rules over every input the declared constraints admit, and the pack's description says so in full — it is not a determination that the controller has discharged Article 22.

  • The Probed Engine (engines/probed.py): The rung for a system whose decision logic cannot be inspected. A logical requirement against a system that exposes decide() but no logic() is searched rather than proved: the engine takes the decisions the system has already made, perturbs their fields — over the values the trace shows, the property's own numeric thresholds and their neighbours — and replays each generated input through the system itself. A counterexample is replayed a second time before it is reported, and one that does not reproduce is a defect in the search, so it is reported not evaluated rather than as a violation. No counterexample within the budget is probed, never proved: the verdict carries what was searched — how many inputs were replayed, the strategy, the seed, and the fields the search could vary — and RequirementResult refuses to be constructed without it, so no rendering can drop it. The same seed replays the same inputs in the same order, so a reported budget can be re-derived. Defaults are 200 replayed inputs at seed 0, both configurable.

  • Binding vs interpretive duties, regulatory scope and decision domain: Each requirement records whether it is a legally binding duty or an interpretive recital/guidance item, any regulatory class it is limited to, and the kinds of decision it is about. The headline names both halves — 6 requirements · 4 binding: 2 observed, 2 unattainable · 2 interpretive: 2 observed — so an interpretive item is reported without being counted as compliance evidence. A class-limited requirement is checked only against a system declared to be in that class via --system-scope; the class is never inferred, so an undeclared system has those requirements reported not applicable. Classes come from one fixed vocabulary — prohibited, high-risk, limited-risk, minimal-risk, general-purpose — which both a pack's scope and a declared --system-scope are checked against, after trimming whitespace and lowercasing and with nothing else guessed. A value outside it is a usage error naming what would have been accepted, so a misspelling on either side cannot become a duty that quietly never matches. A class the vocabulary knows but the chosen pack does not target is not an error: those duties are reported not applicable as a declared mismatch. domains is a second gate on a different axis, working the same way through --system-domain (repeat it for a system that makes more than one kind of decision) and matched by intersection, so one shared domain is enough; a duty declaring no domain reaches every system. One difference matters more than the mechanism: REGULATORY_CLASSES is the EU AI Act's own vocabulary, but no statute defines a list of decision domains, so DECISION_DOMAINS is written in this repository. A pack limiting a duty to a domain must say so in its description, and a not-applicable verdict on that gate reports a classification a pack author made rather than a finding about a statute's reach (docs/authoring-packs.md, the decision-domain vocabulary is yours, not the regulation's).

  • The CLI (cli.py): Five packs ship — Table 7, EU AI Act (Art. 12 & 13), GPAI (EU AI Act Art. 53 & 55), GDPR, ECOA/Reg B — and the CLI runs one against a JSONL decision log. It is installed as the reasonsmith command (pip install reasonsmith) and stays runnable as python -m reasonsmith.cli:

    reasonsmith check --system /path/to/your-decisions.jsonl --pack ecoa --system-domain consumer-credit
    reasonsmith check --system /path/to/your-decisions.jsonl --pack eu_ai_act --system-scope high-risk --html report.html
    reasonsmith validate-pack ecoa eu_ai_act gpai gdpr table7
    reasonsmith --version
    

    check exits 2 when a requirement is violated, 1 on a usage or input error, and 0 otherwise. Unattainable, not applicable and not evaluated are findings to read in the report, not breaches, so none of them changes the exit code. Reports render to plain text, structured JSON (--json), or a self-contained offline HTML report (--html FILE). By default the CLI reads capabilities from the supplied log, and a result resting on that says so rather than speaking for the system; pass --capabilities /path/to/capabilities.txt to instead have the system's maintainers declare what it can emit. The file has one signal name per line; blank lines and whole-line comments whose first nonblank character is # are ignored. The report then says the capabilities were declared. An empty declaration file declares nothing, which is a distinct claim from having no declaration at all, and a malformed line is refused naming the file and the line. --audience {developer,deployer,auditor,regulator,affected-individual} projects the text and HTML renderings for one reader, changing what is shown and never what is claimed; omitted, the full report is printed. --json is deliberately not projected, and its envelope carries a schema_version integer — 1 today — so a consumer can tell one release's shape from another's. It is not the package version: it increments when a key is removed, renamed, or changes type or meaning, and stays put when a key is merely added, so a parser reading the keys it knows is never broken by a version it has not seen. validate-pack validates one or more requirement packs and prints what each contains, exiting 0 for any packs a check run could load and 1 at the first one the loader refuses, naming the file and the requirement at fault; the authoring guide is docs/authoring-packs.md.

  • Machine-Readable & Visual HTML Output: Records, certificates, and reports serialize to dicts (to_dict()), JSON (to_json(indent=None)), and self-contained HTML (render_html()). Each carries the same facts as its text rendering, including its missing-field report and its own limits, so a downstream consumer cannot read a partial document as a complete one. Values outside JSON's own types are stringified rather than raising. Conformance results need no serializer: group_stats() and stratified() already return plain dicts of JSON-native types, so json.dumps(stratified(groups)) is the whole recipe — and an unmeasured metric serialises as null, never 0. The HTML report opens from any file:// path with zero network dependencies, presents the evidence strength lattice, splits binding vs interpretive duties, highlights counterexample trace witnesses for violations, and visually distinguishes unattainable architectural gaps from runtime violations.

  • The Statute Drift Check (drift.py): A maintenance check, not a conformance engine. python -m reasonsmith.drift re-fetches each official statutory document recorded in docs/legal-sources.md and compares the packs' verbatim_text against the live source, collapsing only whitespace (the one thing a printer legitimately changes). Every requirement is match, differ (both strings named) or could-not-verify (the source is unreachable or no longer carries the passage — never a pass), and a pack is never edited automatically. .github/workflows/statute-drift.yml runs it on the first of every month and files a single GitHub issue when anything drifts; the tests run the same check against recorded byte-faithful fixture slices, so the suite needs no network.

  • Dependencies & PyPI: reasonsmith is published on PyPI — pip install reasonsmith is the user install, and the PyPI project page always lists the current release. nesyarena supplies ground-program IR, proof enumeration, and exact WMC (pinned to nesyarena==0.1.0 on PyPI in pyproject.toml); pip install -e ".[dev]" in a venv is the contributor install, pulling the dev tooling in with the source checkout. rtamt, which supplies STL temporal monitoring, and z3-solver, which supplies the SMT solver behind the proved engine, are declared runtime dependencies of reasonsmith, both pinned exactly. torch, by contrast, is an optional dependency of nesyarena (~1GB) and is deliberately not a declared dependency of reasonsmith — it was installed and measured in a separate environment, recorded in RESULTS.md.

Summary of Empirical Findings

Metric / Finding Observed Result Rationale & Mechanism
Stratified Checks (Design A: Confidence Varies) Coverage gap: 0.0000
Fidelity gap: +0.0535
Retained share gap: +0.2802
Top-k proof truncation keeps fixed proof count regardless of confidence scaling. Coverage remains identical across groups; retained share catches the atypical group's loss of value.
Stratified Checks (Design B: Reason Multiplicity Varies) Coverage gap: +0.3000
Fidelity gap: +0.1472
Retained share gap: +0.1129
Cases with more reasons suffer lower coverage under fixed k=1 truncation (a case with 5 reasons retains 1/5th; a case with 2 retains 1/2).
Signal Stability (Drift across windows) Stability score: 0.3333 Under top-1 settings, drift in a single signal silently swaps the stated reason across windows on an unchanged applicant file.

The stratified rows are measured on frozen synthetic cohorts, built to separate the two mechanisms from each other. Whether real atypical cases trip more reasons than typical ones is an empirical question about data this table does not have, and the table does not answer it. Every figure in it is reproduced in RESULTS.md, along with the exact environment and versions, both suites' pass/fail/skip counts with torch installed, and a byte-for-byte diff of two demo runs.

Figures this README takes from the paper rather than from running code — the 273 primary studies, the six Table 7 duties — and the rough ~1GB size of the torch download are not measurements and are not reproduced there.

Who could use this, and what is missing first

Four groups this work is aimed at, and — for each — what is missing before the tool is usable to them. These are gaps, not wishes: every one is stated in a committed document, cited here. A reader from one of these groups should be able to recognise their own blocker.

Not the same list as --audience, and deliberately kept apart. The five audiences above are readers of one report: a projection of a rendering, which ships, works today, and has nothing to do with whether the tool is usable to anyone. The four below are parties who might adopt the project, each with a blocker that is not a rendering. They share two words and neither list refines the other — an insurer is a kind of buyer, an affected individual is a kind of reader, and a regulator appears on both while meaning something different on each. Merging them would have to either invent an adoption blocker for developer and affected-individual, which no committed document states and this page may not manufacture, or drop insurers, who read no report at all.

Insurers pricing exposure on an automated decision system. Missing: a claim that survives past the trace, for most systems and most duties. observed covers exactly the records supplied and establishes nothing about decisions outside them. One escape now exists and is narrow on both axes: an always(f) whose f is a property of one decision is proved over every input a system's exposed logic() admits, so it covers every trace that system can emit — but a system exposing no logic gets no escape at all, and neither does a duty written in any other temporal shape (docs/refinement.md, the trace is a sample; ROADMAP.md §1). Every duty about behaviour over a lifetime — retention, continuous monitoring — is still met by a check over one supplied run wherever that escape does not reach. Also missing: any defence against the insured. The one duty that reads an approximation error reads a number the system declares about itself, which nothing verifies — it rewards the measurement, not the accuracy, and a system that under-reports passes (docs/findings-nesyarena.md, finding 1). And the one fairness property that now ships is invariance under a single named protected variable — a duty about treatment, blind to a proxy and blind to a disparate impact, which is where a large share of the liability actually sits and which no criterion on this evidence model can reach (ROADMAP.md §3; docs/refinement.md, ecoa_reg_b_1002_4_a_no_disparate_treatment).

Regulators wanting a report to stand as supervisory evidence. Missing: authority over the vocabulary a duty's reach is written in. A duty now names the decision domains it is about, and a system that has declared none is reported not applicable rather than satisfied — the ECOA adverse-action duty that once cleared a graph-reachability benchmark issuing no credit no longer reaches it (docs/findings-nesyarena.md, finding 3). But the domain vocabulary is written in this repository and by no regulation, because no statute defines one, so a not-applicable verdict reports a classification a pack author made rather than a finding about the statute's reach — and nothing checks that a system declaring consumer-credit issues credit (docs/authoring-packs.md, the decision-domain vocabulary is yours). Missing too: authority over the refinement. Which formula stands for a clause is a judgement made in this repository and recorded as such — the scope_statements_local_vs_global proxy carried by 12 CFR 1002.9(b)(2) is the pack author's, and the regulation names nothing of the kind (docs/refinement.md). The false positive this section used to report is gone: 12 CFR 1002.9(a)(2) is formalised as the either/or it is, and (b)(2) now carries the trigger the clause states in its own first words — it governs the statement required by paragraph (a)(2)(i) — so a creditor lawfully using the disclosure alternative is no longer reported violated. What replaced it is smaller and is stated rather than hidden: where that creditor's log carries no statement of reasons, the trigger fired nowhere, so (b)(2) is reported not evaluated — naming the antecedent that never fired and the domain that was searched — rather than satisfied (docs/semantics.md §4). That is the honest report of a duty nothing was learned about, and it is still not the honest verdict: not applicable is, per decision, and the result model cannot express one. A supervisor is told the duty was not answered on this log and is not told that the creditor was in the clear.

Auditors running this against a client's system. Missing: reach into systems that are only logs. For any system exposing nothing but a decision trace, observed is the ceiling whatever the pack asks (docs/findings-nesyarena.md, finding 2) — and most audited systems are logs. Missing also: an adversarial default. reasonsmith checks what a system says, not whether it was honest: a declared capability set, a trace and exposed logic are each taken at their word, and where exposed logic and the trace disagree the proof is reported and the trace is never read for that duty (docs/semantics.md §3, §3.5). And no cryptographic signature is verified anywhere in this repository — a signer field is checked for being non-empty (docs/refinement.md, Table 7 Art. 12 row), so the evidence chain is unattested.

Researchers comparing systems or engines. This is the audience the tool is closest to usable for: docs/findings-nesyarena.md is a real run against five nesyarena provenances, and docs/nesyarena-conformance-report.md is its regenerable evidence. Missing: properties worth differentiating a system on, and the fifth pack moved this the wrong way. Twenty-one of the twenty-eight shipped requirements are now presence checks, up from thirteen of nineteen, against three logical, three temporal and one counterfactual one — so a battery of engines mostly agrees by construction, and more so than before packs/gpai.toml shipped. That pack's eight Article 53 and 55 duties are document-production duties, for which presence is the correct refinement and no stronger property exists to write; the breadth is real and it is not depth (ROADMAP.md §4). The two duties that moved show both what closes this gap and how narrow each opening is. 12 CFR 1002.9(b)(2) can now be failed by a plain decision log, because the clause supplies its own list of statements that are insufficient — which is available only where a clause does that, and still establishes nothing about whether what was said instead was adequate. The same clause's second duty differentiates hardest and reaches fewest systems: it compares the reasons a notice states against the reasons the decision's own inference used, measured by the reason-deletion certificate over an artefact the system exposes, and a system that cannot be opened up is reported unattainable rather than returned to the presence check (docs/semantics.md §3, certificate). Missing also: independence. The packs are authored here, so a cross-system comparison measures this repository's refinement as much as it measures the systems — a benchmark needs a pack set whose fourth column someone other than its author has reviewed (docs/refinement.md).

Roadmap

ROADMAP.md is the public backlog: five numbered objectives, each with the gap it closes, a measurable outcome that fails today, and what it depends on — including the one that is deliberately blocked and why. It also lists what is deliberately not planned, so a proposal for one of those gets an answer rather than silence.

The repository has good first issue work sized for a first contribution, and the question that most needs outside answers — which regulation should the next pack cover? — is open in Discussions. CONTRIBUTING.md has the setup, the verification commands and the standing rules.

Limits

Status: Early research software. Nothing here is a compliance guarantee, and none of it is legal advice.

  • A certificate speaks only about the specific program, base interpretation, and query tested.
  • Table 7 completeness checks the form of a record, never the truth or accuracy of its contents.
  • Static capability analysis (unattainable) checks declared or trace-derived signal names, not operational runtime correctness.

Licence

MIT

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Provenance

The following attestation bundles were made for reasonsmith-0.7.0-py3-none-any.whl:

Publisher: publish.yml on eduardstan/reasonsmith

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

0.10.2

2 files

0.9.2

2 files

0.9.1

2 files

0.9.0

2 files

0.8.0

2 files

This release

0.7.0 This release

2 files

0.6.0

2 files

0.5.1

2 files

0.5.0

2 files

0.4.0

2 files

0.2.0

2 files

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