I am acting as the control policy of a reasoning engine, choosing verbs freely and stopping when the decision is sound. I chose Approach A (build a typed relational model, then transport a matched cross-domain pattern and gate it against known failure conditions).

## Working (verbs run)

**1. decompose + lift (problem -> structural core).**
Stripping the domain vocabulary, the meta-model is: many independent agents draw on a shared, rivalrous, slowly-degrading resource with a hard irreversibility threshold; each agent captures the full private benefit of additional use but bears only a fractional (1/N) share of the cumulative cost; use is hard to meter directly; and there is a popularity/"feels fairer" pull toward a single fixed equal allocation. The success bar is dual: stay above the permanent-loss threshold AND keep users viable.

**2. match (search_by_facets — oblique, multi-structure).**
I decomposed into six structural facets (cumulative-loss-past-threshold; private-vs-collective incentive divergence; unobservable/hard-to-meter resource state; rules must adapt vs. fixed-in-advance; graduated sanctions + monitoring sustaining cooperation; equal allocation that feels fair but ignores heterogeneity). Top fused retrievals:
- Prime: `tragedy_of_the_commons` (distinctive, rank 1 fused), with `cooperation`, `governance`, `preference_heterogeneity_and_conflict`, `temporal_decay_and_degradation`.
- Archetype: `commons_governance` (rank 1 fused, appears in 5 of 6 facets).

**3. transport + lower (retrieve full entries, map to the two approaches).**
Pulled the full `tragedy_of_the_commons` prime and `commons_governance` archetype.
- The prime's failure-mode component states the no-intervention trajectory is collapse, and the *success* trajectory is institutional redesign matching governance to problem structure. The empirically validated self-governance pathway is explicitly: clearly-defined boundaries, locally-appropriate rules, **monitoring, graduated sanctions, conflict-resolution, and adaptation as conditions change**. That is a near-verbatim description of Approach B.
- Approach A (uniform, equal, fixed-in-advance quota) maps to a *static* rule. The prime warns the classic privatize-or-fixed-coerce binary is "too strong"; static rules become "both ineffective and unjust" as conditions move.

**4. evaluate-fit (gate each approach against known failure conditions).**
- Approach A is gated against the archetype's **"Rigid quota failure"** failure mode: "use limits that ignore changing conditions"; mitigation = "resource-condition triggers, periodic review, and exception processes." A has none of these. Against a slowly-degrading resource with an irreversible threshold, a fixed equal quota set in advance has no mechanism to detect that the resource is approaching the threshold and tighten before it is crossed. The dual success criterion (stay above threshold) is therefore not robustly met by A.
- Apparent objection favoring A: "use is hard to meter directly," which seems to break B's monitoring requirement. Gate check: the archetype is explicit that the **Monitoring Signal** observes *resource condition* (stock/state), not necessarily per-user metering, and "can be technical, social, institutional, or audit-based." B monitors the resource's state, which is exactly the move that works when individual use is hard to meter. So the metering difficulty does not disqualify B; if anything it disqualifies A, because A's fixed per-user quota assumes a stable correct number that can't be re-derived as conditions change.
- Gate the "feels fairer / popular at the next meeting" consideration: this is a legitimacy/preference signal, not a viability mechanism. Equal-split fairness sits under `preference_heterogeneity_and_conflict` and the symmetry-fairness allocation pattern — it improves acceptability but does nothing to keep the resource above the irreversible threshold. The prime is clear that the tragedy is *structural, not moral*: exhortation and a fair-feeling rule do not change the (1/N) incentive that drives overshoot. Popularity cannot be the decisive factor when the binding constraint is irreversibility. Note B can still *incorporate* equal baseline shares plus participatory rulemaking, capturing most of the fairness appeal without sacrificing adaptivity — so the fairness pull is not a true reason to prefer A.

**5. reconcile + prune.**
Both criteria (threshold-safety and user viability) are jointly satisfiable only by a rule that (a) watches the resource and tightens before the irreversible point, (b) deters overuse proportionally so restraint is not individually irrational, and (c) revises itself as conditions change. That is Approach B. Approach A optimizes legibility and felt-fairness at the cost of the one property the irreversible threshold makes non-negotiable: the ability to respond before collapse. STOP — decision is sound.

===DECISION_BEGIN===
DECISIVE_FACTOR: Because the resource degrades slowly toward a point of permanent, irreversible loss, the governing rule must be able to sense the resource's condition and tighten use before that point is crossed — something a single number fixed in advance cannot do.
CHOICE: B
JUSTIFICATION: A fixed equal quota set in advance has no way to notice the resource approaching the point of no return and adjust, so a wrong guess becomes an irreversible loss that also wipes out every user. Watching the resource's actual condition, escalating consequences for overuse, and revising the limits together as conditions change is what keeps the resource above the danger point while still letting people use it. The equal-split rule may feel fairer and win the vote, but feeling fair does not stop depletion, and the adaptive approach can still start from equal shares while adding the safeguards that prevent collapse.
===DECISION_END===
