sl-auditor

name

sl-auditor

description

Audits an existing Squeeze Loop (SL) for soundness — checking whether a target loop is truly compliant (pairwise-disjoint authority pairs, physically barriered contexts, gate-defined "done", a genuine executable lower bound, and demonstrated catching of coherent-and-wrong) or is quietly collapsing into a rubber stamp. It applies the squeeze's own discipline to the loop under audit: it maps the actual (upper, lower) authority pairs and hunts for an actor certifying its own work; probes whether each context barrier is physical or merely honorary; confirms an executable oracle disjoint from the actor it judges; checks Gate A / Gate B / Gate C are present and load-bearing; seeds coherent-and-wrong artifacts to calibrate the monitors (flag rate not zero, not saturated); audits the loop's accumulated learned skills VIA the sl-monitoring-sl pattern; checks each known collapse mode is blocked by a stabilizer; and routes whatever an internal audit cannot self-certify to a disjoint base (external / cross-provider / human reviewer). Emits a per-dimension findings report with severities. Where the target carries an SL-1.0 `*.sl.json` self-description (owned by its coordinator), it ingests that and runs `sl-internal/scripts/sl_disjointness_check.py` as the mechanical floor of the disjointness/barrier/oracle dimensions (a floor, not a ceiling), and runs the cross-loop source-of-truth check when the target is itself a monitor of another loop. Use when asked to "audit a squeeze loop", "review an existing SL", "is this squeeze loop sound", "check my SL for collapse", "does this loop actually have disjoint authorities", "is the barrier real or honorary", "who certifies the certifier", "is done gate-defined or self- reported", "is this monitor a rubber stamp", "validate an sl.json / run the disjointness checker", or "is my loop quietly collapsing".

sl-auditor — auditing an existing Squeeze Loop

This skill is an audit methodology for a target Squeeze Loop (SL). It does not design or operate a loop; it interrogates one that already runs and decides whether it is actually sound or only looks sound. The method is the squeeze turned on itself: every claim the target loop makes about its own soundness is held between an upper bound (the compliance conditions C1–C4 and the stabilizer set the loop is supposed to satisfy) and a lower bound (what the loop's contexts, oracles, and gates actually contain and run when you inspect them). A loop is "in-band" only as a reading of its design intent that its inspected reality does not refute.

It depends on a sibling skill. The soft-output / learned-skill dimension of an audit IS the sl-monitoring-sl pattern — see Dimension 6. This skill does not re-derive that machinery; it invokes it. For conceptual background on a single squeeze (the actor-between-two-bounds picture), the sl-internal skill may be consulted if present.

The one-paragraph model being audited

A squeeze loop holds every actor between an upper bound U (a citable, normative soft truth — the strongest claim the actor may make) and a lower bound L (an executable hard truth — a runnable oracle whose verdict the actor cannot alter). A deliverable is in-band only if it is a reading of U that L does not refute; coherent-and-wrong is precisely a deliverable that L's proxy accepts while it violates U's intent. The load-bearing rule is disjointness: every actor answers to a different (U, L) pair, so no single actor's evidence base suffices to certify the deliverable and each actor's characteristic blind spot is caught by an actor that cannot share it. An audit checks that this structure is real and not honorary.

The compliance contract the audit checks against (the upper bound)

The target loop is squeeze-loop compliant iff:

• (C1) Disjointness. The authority pairs are pairwise distinct, chosen so the intersection of the in-band sets is the correct deliverable while no single pair suffices to certify it.
• (C2) Catchability. For every actor and every characteristic failure that survives its own squeeze, some other actor's pair makes that failure detectable.
• (C3) Physical barriers. At delegation time each actor's context contains exactly its authorities and the interfaces it must exercise; denied evidence (above all, the implementation, for the actors who judge it) is absent from the context, not merely off-limits by instruction.
• (C4) Gate-defined done. An item is done iff a fixed set of machine-checked gates passes; no actor's self-report contributes to the definition.

The audit produces a verdict per condition, plus the residual that no internal check can settle (Dimension 8).

How to read the rest of this skill

Dimensions 1–7 are the audit checklist. Each is the squeeze's own discipline pointed at the target. Dimension 8 is the irreducible limit (the disjoint base). Dimension 9 is the output form. Run them in order: a loop that fails Dimension 1 (no real disjointness) cannot be rescued by passing the later ones.

The audit's structured input and mechanical floor. A target loop built or maintained under the current SL skills carries its own SL-1.0 *.sl.json self-description, owned by its coordinator (see sl-builder / sl-internal). Ask for it first: it is the registry of sources, actor bounds-by-id, and barriers the later dimensions interrogate. Run sl-internal/scripts/sl_disjointness_check.py <target>.sl.json to mechanize the floor of **D1 (self-certification incl. a self-owned oracle, shared evidence, single-pair-suffices), D2 (barrier consistency

• missing-required barrier), C2 (catchability)** and the endogeneity / terminus predicates. In two-file mode (<controlling> <base>) it also runs D6 cross-loop source-of-truth. The checker's dimension tags match this skill's numbering.

Render the loop while you are here (idempotent). For each loop you ingest, if docs/img/<id>.{png,svg} are not already on disk, generate them — sl-internal/scripts/sl2plantuml.py <target>.sl.json -o docs/img/<id>.png and the same with --svg -o docs/img/<id>.svg (add --direction tb for a large, dense loop); <id> is the loop's id (the *.sl.json filename stem). The diagram is a durable visual the audit reads at a glance: the colour/glyph channel surfaces the cast roles, the point-vs-invariant oracles, an endogenous bound (red dashed ⚠ overlay — a bound-level D1 finding), the ✗ must-not-see barriers (D2), and the catchability edges (C2). Skip if both files already exist — do not clobber a coordinator's committed diagram; the render is a convenience artifact, never an authority. In two-file / nested mode render the base loop too (docs/img/<base-id>.{png,svg}).

Two cautions, both load-bearing:

• The *.sl.json is a claim, not the territory. It is the loop's self-description, and a loop can be coherent-and-wrong about itself (Dimension 8). A checker PASS is necessary, not sufficient — you still map the real pairs against the actual delegation prompts and tool permissions (Dimension 1, step 1), exactly as you would distrust an org chart.
• The checker is a floor, not a ceiling. It mechanizes the structural dimensions above; it does not decide D3 (oracle existence / immutability / runnability), D4 (gates / done), D5 (coherent-and-wrong seeding) or D7 (stabilizer ablation) — those stay manual. And it cannot credit a barrier that is real but undeclared, nor judge whether the registry matches the actual delegation prompts. Never read a green as the whole audit.

---

Dimension 1 — Disjointness audit (C1)

Question: are the (upper, lower) authority pairs pairwise distinct, and does any actor answer to a bound it can itself relieve or edit?

Procedure.

0. Ingest the self-description and run the checker. Obtain the coordinator-owned *.sl.json and run sl-internal/scripts/sl_disjointness_check.py over it. This mechanizes the floor of steps 2–3 (shared-evidence and self-certification, the latter as produces ∪ produced_by ∩ bound_sources) plus referential integrity. Record its verdicts — then keep going: a PASS here is the floor, and the registry is a claim to be checked against reality in step 1. While ingesting, render the loop's diagram to docs/img/<id>.{png,svg} if not already present (see the mechanical floor above) — a visual that surfaces the cast, the barriers, and any endogenous bound for the dimensions that follow.

1. Map the real pairs. For every actor in the target loop, write down its actual (U_i, L_i) — the authority that squeezes it from above and the executable that squeezes it from below — as enforced, not as documented. Distrust the org chart and the *.sl.json; read the delegation prompts and tool permissions, and flag any divergence between the registry and what the prompts actually contain (that divergence is itself a self-description-drift finding — Dimension 8).

2. Pairwise-distinctness check. Compare pairs. Two actors holding the same (U, L) is the shared-evidence collapse: an error in that base propagates unchecked because no actor reads from a different one. Flag any duplicate pair.

3. Self-certification hunt — the central probe. For each actor, ask: can this actor edit, author, soften, or relieve the very bound that is supposed to catch it? Concretely:

   • Does the implementer edit or author its own acceptance tests / oracle?
   • Does the actor that judges a deliverable also produce it?
   • Can an actor weaken the obligation clause it is later checked against?

   Any "yes" is self-judging — the same blind spot, doubled — and is a high-severity finding regardless of how the loop is otherwise structured.

4. Sufficiency check (the subtle half of C1). Even with distinct pairs, C1 demands that no single pair suffices to certify the deliverable. If one actor's evidence base alone is enough to bless the output, the rest of the cast is decorative. Confirm the intersection is what's correct, not any one pair.

Pass = pairs pairwise distinct, no actor relieves its own bound, certification requires the intersection. Fail = any duplicate pair, any self-certifying actor, or any single-pair-suffices path.

---

Dimension 2 — Barrier audit (C3)

Question: are the context barriers physical (the implementation / evidence is genuinely absent from the relevant actor's context) or merely honorary (an instruction not to look)?

The key probe — read the delegation prompt, not the policy doc:

• Can the exerciser / verifier see the implementation? If the diff, the source, or the internals are present in the judging actor's context, the barrier is honorary even if the prompt says "do not rely on the code." An agent that has the internals in context will eventually use them.
• Can the judge see the thing it judges, from a disjoint source? The verifier's authority must be the raw ground truth (the source re-opened at its anchor, the artifact re-run) — never the producer's account of it (the writer's notes, the records' interpretation fields). If the judge reads the producer's interpretation, the barrier between author and judge is honorary.
• Anchoring tell. When the exerciser's negatives or the drivers mirror the implementation's quirks, the barrier has already leaked: the exerciser anchored to the implementation rather than to U. This is the honorary-barrier collapse and is directly measurable by the barrier ablation (Dimension 5 / Dimension 7).

Pass = denied evidence is structurally absent from each judging context. Fail = "off-limits by instruction" anywhere a barrier is load-bearing, or any sign of implementation-anchoring in the exerciser/verifier.

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Dimension 3 — Lower-bound audit (the executable oracle)

Question: is there a genuine executable oracle L whose verdict the actor cannot alter, and is it disjoint from the actor (not the actor's own check)?

Procedure.

1. Existence. Identify, for each actor, the runnable L: a pure function, a committed verdict cache, a conformance suite, a re-run of an artifact, a type/proof checker. If there is no executable lower bound, the loop cannot catch coherent-and-wrong by construction — coherent-and-wrong is exactly the class only L rules out. Record this as a structural defect, not a gap.
2. Immutability. Confirm the actor cannot edit L or its inputs to make itself pass (tie back to the self-certification hunt in Dimension 1). An oracle the actor can tune is not a lower bound.
3. Disjointness of L. The oracle must be authored/held by someone other than the actor it bounds. The implementer's own unit tests are not a lower bound for the implementer; they share its blind spot. In the *.sl.json this is the executable_oracle source's produced_by: if it equals the actor that reads it as lower_bound, the checker flags it (self-owned L). Confirm executable is set and the verdict is genuinely re-runnable, not a recorded assertion.
4. Honesty of availability. If a sub-loop's L is not actually runnable in the audit environment, say so — DEPENDENCY UNMET — and do not record a pass for that sub-loop. Never fake a green for an unaudited oracle. (This mirrors the sl-monitoring-sl oracle-availability discipline.)

Pass = every actor has a disjoint, immutable, runnable L. Fail = a missing L (structural — the loop is soft-only), a self-owned L, or an unrunnable L reported as passing.

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Dimension 4 — Gate audit (C4) — is "done" machine-defined?

Question: is done defined only by machine gates, or does it rest on an agent's report of success? Are Gate A, Gate B, Gate C present and load-bearing?

The canonical gate stack (name the target's analogues):

• Gate A — editorial approval of the plan, before code. A disjoint judge amends, cuts, or sharpens the plan; it judges the higher-risk half before any source is written. A rubber stamp here makes the upper bound fictional — the approval must demonstrably alter or contest the plan, not echo it. Confirm no source edit ever flows from an unapproved (DRAFT) plan.
• Gate B — machine-checked acceptance. The build/compile is green; every claim is bound; every number is machine-generated; conservation invariants (additivity, standing counts, determinism re-runs) hold. This is the per-plane hard check.
• Gate C — coverage / no-blend / coherent-and-wrong. Each obligation clause of the property maps to a passing check; the planes are not blended (one plane's weak check standing in for another); and the gate is calibrated by seeded falsifications (Dimension 5). Gate C is the one carrying the soundness argument where authority is authored — confirm it is real, not a label.

The decisive test for C4: trace one item to DONE and ask what actually ended it. If the answer is "the agent reported success" or "it reads well / compiles," that is the self-declared-done collapse — reading well is what the dominant failure looks like. Done must reduce to gates passing, witnessed by independently authored evidence.

Pass = done is gate-defined; A/B/C all present and load-bearing. Fail = any self-report in the done definition; a missing or vacuous gate; Gate A that never amends; Gate C without calibration.

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Dimension 5 — Coherent-and-wrong probes (monitor calibration)

Question: does the loop actually catch coherent-and-wrong, or is its monitor a rubber stamp that flags nothing?

A monitor that flags nothing has stopped checking; a monitor that flags everything is saturated (over-claiming, or auditing a uniformly-bad population). A healthy monitor discriminates — it flags a strict, nonempty subset.

Procedure.

1. Seed plausible-but-wrong artifacts. Plant a controlled set of coherent-and-wrong inputs the loop should catch: a valid result that proves an adjacent / weaker property; a doc-vs-runtime blend (compliant documentation over broken behaviour); an over-stated comparative claim that survives an abstract read but not a full-text read; a result that holds on one seed but not on a perturbed one; a relabeling (hard in-scope work parked in an exempt bucket) and a fabrication (work invented on a trivial input). (Concrete primitives in this repo: verify/perturbation.py perturbs the anchor/seed; verify/category_overreach.py tests a generated category on every instance. Generic addendum gates in sl-internal/scripts/: refutation_probe.py (A2 — an exemption without an attached constructive-negation probe is a gate failure; verdict flips when the claimed-missing piece is supplied ⇒ REJECT) and conservation_gate.py (A6 — strip the added kind-X and require the remainder to equal the original input; catches a mutated/fabricated Y and trivial-input fabrication). Each carries a --selftest.)
2. Run the loop on the seeds. Every seed must be caught with the right verdict and the right localization — a verification run that would not have caught a planted falsehood has not verified anything. A missed seed voids the run.
3. Flag-rate calibration. Across the population the monitor audits, assert 0 < flagged < total (the discriminating band). A permanent zero is a rubber stamp; flagging everything is saturation. (Primitive: verify/flag_rate.py, which asserts each monitoring plane sits in the band and refuses a zero external-catch count.)

Pass = all seeds caught with correct verdicts; every monitor in the discriminating band. Fail = any missed seed; any permanently rubber-stamping or saturated monitor.

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Dimension 6 — Soft-output / skill audit — VIA sl-monitoring-sl

This is where the auditor depends on the sl-monitoring-sl skill. State this plainly in the report: the dimension that audits a target loop's learned, soft outputs IS the sl-monitoring-sl pattern, invoked here, not re-implemented.

Question: if the target loop accumulates learned skills / heuristics, are they in-band — readings the loop's own bounds do not refute on any reachable input — or has it consolidated coherent-and-wrong skills (right on the common case, silently wrong on a governed exception)?

Procedure (delegate to sl-monitoring-sl):

1. Treat the audit as another squeeze. The monitor's upper bound is the base loop's U; its lower bound is the base loop's executable L; its forbidden move is reading the deciding actor's rationale for the skill or editing the base loop's implementation. Squeeze each accumulated skill from a disjoint base, not from the actor that wrote it (its producer shares the skill's blind spot).
2. Classify each skill by kind and run the matching check (Gate S):
   • ignore-signal ("treat signal X as noise") — the high-risk kind; it inverts the oracle's relevance. Run the trigger test (perturb X, see if L's verdict moves); repair by carving a bound-deferring exception on the values where ignoring X diverges from L. Preserve the valid core.
   • defer-to-oracle ("on case S, take the oracle-sanctioned action A_S") — consistent by construction; run the validity test (confirm L actually distinguishes S and sanctions A_S); prune if spurious.
3. Discriminate. A healthy audit leaves the defer-to-oracle skills untouched and flags only the over-reaching ignore-signal skills — most untouched, few carved. A skill monitor that flags everything or nothing is miscalibrated (ties back to Dimension 5).
4. Verdicts are Gate S's: PASS / CARVE-OUT / REJECT (loud-fail). Every carve-out cites the exact U clause it defers to; carve-outs only ever make a skill more faithful to U, never license an action U forbids; every fix is traceable to a monitor finding. If a base loop's L is not runnable, report DEPENDENCY UNMET — never fake a PASS for an unaudited loop.

Cross-loop source-of-truth check (when the target is itself a monitor / nested loop). If the target controls a base loop, its disjointness from that base is auditable as a set operation, not just narrated. Have the target's coordinator request the base loop's *.sl.json (request/response; only the registry crosses — never the base's implementation or rationale, so the monitor's forbidden move stays intact) and verify: target.bound_sources ∩ base.internal_sources = ∅ (base-internal = produced_by != null or provenance ∈ {endogenous, internal}; the only sanctioned base→target link is a sub_loop bridge row), and no shared source id carries a conflicting (type, provenance, produced_by) (legitimate only for the genuinely-same exogenous authority both levels cite). A non-empty intersection is the cross-level form of self-certification/blend — the monitor bounding itself on evidence the base produced — and is a CRITICAL finding. If the base coordinator does not forward its registry, record the cross-level disjointness as asserted, not verified — never a silent PASS. See sl-monitoring-sl for this check's definition.

See sl-monitoring-sl/SKILL.md for the full Gate S procedure, the two worked examples, and the non-negotiable discipline. Do not re-derive it here — invoke it.

Pass = every accumulated skill is PASS or carved/pruned to in-band, with the monitor discriminating. Fail = a self-judged skill store (the base loop validating its own learned rules), an uncarved over-reaching skill, or a soft skill silently standing in for the authoritative upper bound (the no-blend rule pushed down one level).

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Dimension 7 — Stabilizer audit (each collapse mode is blocked)

Question: for each known collapse mode (an event where an actor relieves its own squeeze), is the blocking stabilizer present and load-bearing in the target?

Walk the collapse-mode table; for each, find the structural rule that blocks it and confirm it is real:

Collapse mode	Symptom to look for	Blocked by
Self-judging	implementer edits/authors its own acceptance; tests pass suspiciously fast	forbidden moves load-bearing; physical barriers
Shared evidence	two actors hold identical (U,L); an error propagates unchecked	the C1 disjointness audit (Dim 1)
Honorary barrier	internals in the judge's context; drivers mirror implementation quirks	barriers physical, not honorary (Dim 2)
Self-declared done	"the agent reported success" ends the item	done gate-defined (Dim 4)
Absorbed surprise	a local workaround; the loop's model of reality drifts	surprise is routed, never absorbed
Rubber-stamp approval	plans approved verbatim, instantly	editorial approval gates the plan, must amend/cut/sharpen
Coherent-and-wrong	a valid result proving an adjacent, weaker property	independence-is-the-soundness-argument + Gate C calibration
Weakened clause	"it proves now" after the obligation was quietly softened	strictness has a safe direction (stricter, never weaker)
Regression by rationalization	"that diff is expected"	conservation laws rerun after every item
Vacuous acceptance	a proof of a vacuous / adjacent theorem; an empty obligation set passes	Gate C axiom/coverage audit (each obligation clause maps to a passing check)
Unpinned reality	design built on assumed tool behaviour	pin reality before building on it
Scope blur	silent over-claiming; unclassified escape hatches	honest scope is a deliverable (NOT-claims, residual ledger)
Relabel-to-exempt	in-scope work parked in residual/out-of-scope/BLOCKED/"tool limitation"; artifact-only gates pass	each exemption is evidence-bearing; scripts/refutation_probe.py (supply the claimed-impossible piece, re-run; flip ⇒ REJECT)
Emergent obligation exempted	a cross-cutting obligation with no local move silently lands in the residue bucket	name the emergent class as a first-class move before dispatch (Dim 1 / sl-builder)
Trivial-input fabrication	a trivial/empty input yields a non-trivial deliverable; Y mutated	scripts/conservation_gate.py (strip X, remainder must equal input); triage trivial inputs away from producers
Over-broad coordinator triage	a one-signal "skip the cheap inputs" fast-path drops a whole real-work class	scripts/triage_audit.py (triage vs ground-truth reference; carve on dropped real work) — the monitor's remit covers the coordinator's triage, not just producers' skills
Orphan change	an edit with no plan, no gap, no authority behind it	traceability is an acceptance criterion

The barrier ablation is the master stabilizer test. Run the target with the barrier on and off: with the barrier on the squeeze should catch the seeded coherent-and-wrong implementers; with the barrier off (the exerciser anchored to the implementation) the catch rate collapses. A loop whose catch rate does not move when you remove the barrier never had a load-bearing barrier — the stabilizer was decorative.

Pass = every collapse mode has a present, load-bearing blocker; the barrier ablation moves the catch rate. Fail = any unblocked mode, or any "blocker" that is documentation rather than structure.

---

Dimension 8 — The irreducible limit (route to a disjoint base)

Name this honestly: an internal audit cannot self-certify the residual. Where authority is authored (no external spec to diff against), the only defense against coherent-and-wrong is the independence of the judge from the producer — and an audit run by the loop's own actors shares the loop's blind spot exactly as a self-judged skill does. Two residuals always escape internal mechanization:

• Soft-vs-soft faithfulness. "Is the framing / interpretation faithful to the evidence?" has no executable lower bound; no machine gate refutes "the summary over-emphasizes X." This must be routed to a disjoint editorial judge (the standing Gate A), with a current review on file (a recorded review whose hash matches the artifact as it stands now — a stale review is no review). Primitive: verify/claim_consistency.py mechanizes only the return of a known framing defect; verify/editorial_gate.py enforces that a fresh disjoint judgment exists. Coverage of the mechanized part is a floor, not a ceiling.
• Self-description drift. A loop can go coherent-and-wrong about itself — its apparatus changes but its description of its apparatus does not (verify/apparatus_described.py catches the named-vs-present proxy; accurate description still needs the disjoint judge).

Routing rule. The disjoint base should be cross-provider or human — a same-provider-family judge shares the author's blind spot and counts only as partial disjointness. Capability and disjointness are different axes and trade off: the gold standard is a judge that is both capable and cross-provider; a truly cross-provider but weak judge is recorded non-authoritative (it must pass known-contradiction / known-consistent controls first), and a capable same-family judge is recorded partial. Report which you have and what is still pending — you cannot delete the disjoint reviewer, only make its bookkeeping mechanical.

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Dimension 9 — Output: the audit report

Produce a structured report, not a verdict. Form:

SL AUDIT — <target loop name>           date: <YYYY-MM-DD>

SL-1.0 INPUT
  *.sl.json present?          YES | NO (audit by inspection only)
  sl_disjointness_check.py    PASS | FAIL | N/A       — mechanical floor (D1/D2/D3 + endogeneity); floor, not ceiling
  diagram rendered            docs/img/<id>.{png,svg}  RENDERED | ALREADY-PRESENT | N/A (no *.sl.json)

PER-DIMENSION FINDINGS
  D1 Disjointness (C1)        PASS | FAIL | PARTIAL   — <one line + evidence>; registry-vs-prompts drift?
  D2 Barrier (C3)             PASS | FAIL | PARTIAL   — physical or honorary? <probe result>
  D3 Lower bound (oracle)     PASS | FAIL | DEP-UNMET — disjoint, immutable, runnable?
  D4 Gates / done (C4)        PASS | FAIL             — Gate A/B/C present & load-bearing?
  D5 Coherent-and-wrong       PASS | FAIL             — seeds caught? flag rate in band?
  D6 Skills (via sl-monitoring-sl)  PASS | CARVE | REJECT  — Gate S verdicts per skill
     cross-loop sources       PASS | FAIL | ASSERTED  — if target is a monitor: registries verified-disjoint?
  D7 Stabilizers              PASS | FAIL             — collapse modes blocked? barrier ablation moved?
  C2 Catchability             (implied by D1+D5)      — every char. failure caught by another actor?

SEVERITY
  CRITICAL  — structural: self-certifying actor, no executable L, honorary barrier
              on a load-bearing edge, self-declared done. The loop is collapsing.
  MAJOR     — a present-but-weak gate, a miscalibrated monitor, an uncarved
              over-reaching skill, a missing stabilizer.
  MINOR     — bookkeeping: stale editorial review, undescribed apparatus, traceability gaps.

DISJOINT-BASE ROUTING (the residual)
  - Soft-vs-soft faithfulness  -> <cross-provider | human judge>; status: <on file / stale / pending>
  - Self-description accuracy   -> standing Gate A; status: <...>
  - Any DEPENDENCY-UNMET oracle -> <named>, NOT certified by this audit.

Discipline for the report itself (the audit obeys the squeeze it audits):

• Loud-fail, never approximate. An undecidable dimension is reported DEPENDENCY UNMET or routed to the disjoint base — never quietly passed.
• Ground every finding. Cite the delegation prompt / oracle / gate that evidences it; a finding with no evidence is hearsay.
• Safe direction. When unsure, downgrade the loop's claimed soundness, never inflate it — understating a loop's health is a style choice; overstating it is the dominant failure wearing its best suit.
• Do not self-certify the residual. The audit's own soft-vs-soft judgments are themselves routed to a disjoint base; an internal audit that claims to have certified everything has just demonstrated the failure it was hunting for.