WORKING (verbs run, in order):

**match** — Queried the engine with the domain-stripped meta-model: "many independent actors draw on a shared finite stock that degrades and is permanently destroyed past a threshold; individual incentives to extract diverge from collective survival; usage is hard to observe." Top distinctive hit: the common-pool resource depletion pattern (the structural misalignment where each user captures the full private benefit of one more unit but bears only a 1/N share of the collective cost). Family neighborhood: free-riding, public goods, scarcity, mechanism design.

**match (search_by_facets)** — Because the problem is oblique (it bundles four distinct structures: shared-rivalrous depletion, an irreversible threshold, low observability, and fixed-vs-adaptive rule design), I decomposed into facets and retrieved each separately:
- "shared resource depleted by many independent users with divergent incentives" → the commons-depletion pattern, free-riding, public goods.
- "an irreversible threshold past which the system is permanently lost" → irreversibility, threshold/criticality, temporal decay.
- "actions hard to observe or meter directly" → observer-effect / observability-limit family.
- "governance that adapts as conditions change with graduated enforcement" → governance, informal enforcement, institutions.
- "fixed uniform rule set in advance vs a feedback-driven adaptive rule" → the adaptive-regulator pattern (maintain an essential variable within viable bounds by re-searching configurations as disturbances arrive), system archetypes.
The fused ranking put the adaptive-regulator pattern at the top, alongside the irreversibility and observability facets — confirming the problem is NOT just "a commons" but "a commons with an irreversible cliff under poor observability."

**lift** — Stepped to the underlying structure. The core diagnosis: this is the classic shared-pool depletion structure. Its own internal logic already adjudicates the two approaches. The accumulated scholarship on this exact pattern is explicit that the naive remedy (a single fixed, uniform rule imposed in advance) is the *weak* pathway, and that durable success comes from a bundle of: condition-monitoring, graduated (proportional) sanctions, and a collective process that revises the rules as conditions change. Approach B is a near-verbatim instantiation of that success bundle; Approach A is the fixed-uniform-rule pathway flagged as failure-prone because it cannot track a moving target.

**transport + lower** — Mapped the retrieved logic onto the situation's roles. Essential variable = resource stock; viable bounds = "above the point of permanent loss" while "users stay viable." A fixed quota set in advance is a single control configuration; the adaptive-regulator logic says a single fixed configuration is robust only if it already matches every disturbance it will face. Here disturbances (demand, weather, entry/exit of users, slow degradation) vary over time and the stock state changes — so a one-shot uniform quota has no way to tighten before a slow drift crosses the cliff, and no way to loosen when slack exists (starving viability). Monitoring + graduated sanctions + collective adjustment supply exactly the requisite range of corrective moves.

**evaluate-fit (gate against known failure conditions)** — Ran both approaches against the catalog's documented failure modes.
- *Irreversibility gate:* the resource has a one-way cliff (permanent loss past a threshold), and reversal cost is effectively infinite. The correct posture under an irreversible downside is precaution + early-warning monitoring of approach-to-threshold signals + the ability to act before the crossing. Approach A has NO sensing channel and NO mid-course correction — if the fixed quota is even slightly too generous given slow degradation, the system drifts silently into permanent loss with no chance to catch it. This is the decisive disqualifier for A.
- *Observability gate:* "use is hard to meter directly." This actually weakens A further, not B: a fixed per-user quota presumes you can verify per-user use, which is exactly what's hard. Approach B governs on *resource-state* monitoring (you watch the stock's condition, which is observable) plus graduated sanctions for detected over-use, so it degrades gracefully under imperfect metering rather than depending on per-user metering it cannot get.
- *Legitimacy / burnout / capture gates (B's risks):* the catalog flags that B can fail via illegitimate enforcement, capture by powerful users, or surveillance overreach. These are real but *mitigable by design* (proportional sanctions, participatory revision, equity review) and, crucially, they are not terminal — they degrade fairness, not survival. A's failure mode (silent overshoot of an irreversible threshold) IS terminal against the stated success criterion.
- *Equal-quota equity check:* A's one virtue is simplicity/equal treatment, but a uniform fixed quota ignores heterogeneous needs and changing conditions, so it tends to make some users non-viable while still not guaranteeing the stock stays above the cliff — failing both halves of the success criterion at once.

**reconcile** — Both criteria (stock stays above permanent-loss point AND users remain viable) require *tracking a moving target with an irreversible downside*. Only an arrangement that senses the resource state and corrects course can hold both simultaneously. A fixed-in-advance uniform rule is a guess locked in before the disturbances are known; against an irreversible cliff, a guess with no correction loop is an unacceptable bet. STOP — decision is sound.

===DECISION_BEGIN===
DECISIVE_FACTOR: The resource has a one-way threshold of permanent loss, so the governing rule must sense the resource's actual condition and correct course before the cliff — which a rule fixed in advance, with no feedback, structurally cannot do.
CHOICE: B
JUSTIFICATION: Because crossing the depletion threshold is permanent and unrecoverable, the rule has to detect when the resource is heading toward that point and adjust before it is reached; a single quota locked in beforehand has no way to notice slow drift or react to changing conditions, so even a small misjudgment can quietly destroy the resource. Watching the resource's state, escalating consequences in proportion to over-use, and revising allocations as conditions change keeps the resource above the danger point while still leaving users enough to stay viable. It also handles the fact that individual use is hard to measure, since it governs on the observable health of the shared resource rather than on per-user metering that cannot be verified.
===DECISION_END===
