# Working — FC3, condition B (free verb library)

I acted as the control policy, choosing verbs freely from the v1 library and stopping when the
decision was sound. I called the encyclopedia tools at the retrieval and gate steps.

## match (retrieve)
Anchored the problem to the catalog two ways.

- `search_by_facets` over five facets of the situation (depletable shared resource with an
  irreversible collapse threshold; private-vs-collective incentive split; hard-to-meter state;
  one uniform fixed rule for heterogeneous users; monitoring + graduated sanctions + collective
  adjustment). Per-facet and fused rankings put **`commons_governance`** at the top of the
  archetype fusion (rrf 0.0328) and **`tragedy_of_the_commons`** at the top of the prime fusion —
  the only *distinctive*-band prime among the leaders (percentile 0.69). Supporting neighborhood:
  `social_dilemma`, `free_riding`, `scarcity`, `mechanism_design_and_incentive_structure`,
  `irreversibility`, `monitoring`, `governance`, `institutional_lag`.
- `search_prime` with the domain-stripped meta-model corroborated the same neighborhood
  (`cooperation`/`social_dilemma`/`tragedy_of_the_commons`/`free_riding`).

Recorded source-prime overlap: `commons_governance` ← {tragedy_of_the_commons, public_goods,
resource_management}. Post-condition met (≥1 candidate with overlap). No retrieval miss; the
neighborhood is crowded but the load-bearing prime is distinctive, so no disambiguation problem.

## salience-rank + prune
Operative subset (ablation test — would removing it change the recommendation?):

- **tragedy_of_the_commons** — *load_bearing.* Supplies the core structural diagnosis: each user
  captures the full private benefit of one more unit of use but bears only ~1/N of the cumulative
  cost, so individually rational use overshoots the sustainable yield. This is exactly the
  situation. Remove it and the whole framing collapses.
- **irreversibility / threshold (margin_of_safety)** — *load_bearing.* "Past a threshold,
  permanently lost" means the cost of a wrong rule is asymmetric and uncorrectable. This drives
  the need for a safety margin and the ability to pull back before collapse.
- **observability / metering ("hard to meter directly")** — *load_bearing.* The signal you can
  act on is the *resource's state*, not each user's individual use. This is the single fact that
  most separates the two approaches.
- **preference_heterogeneity** — *load_bearing.* Users are not identical; a single number fixed
  for everyone in advance will mis-fit them.
- `public_goods`, `free_riding`, `mechanism_design` — *context* (pruned to background): they name
  the same dilemma family but add nothing past tragedy_of_the_commons here.

## compose (typed relational model)
- Nodes: {many independent users (kind: agents)}, {shared resource w/ slow degradation + hard
  collapse threshold (kind: stock)}, {use/extraction decisions (kind: actions)}, {resource-state
  signal (kind: observable, noisy/laggy)}, {governance rule (kind: controller)}.
- Edges: users —extract→ resource (annotation: tragedy_of_the_commons, 1/N cost-share);
  resource —state→ signal (annotation: observability constraint, metering is indirect);
  governance —constrains→ users (the lever); resource-state —feeds back→ governance (present only
  under Approach B). Every operative prime appears as an annotation (referential integrity holds).

## lift (L1) — situation → meta-model
Stripped to skeleton: *N independent controllers act on one shared stock through a feedback path
that is (a) noisy/indirect and (b) has an absorbing failure state. A controller is either
open-loop (set once, no state feedback) or closed-loop (senses stock, adjusts, escalates
response).* Every role has a witness in the model; no domain terms remain.

The meta-model immediately exposes the decision: **Approach A is an open-loop controller on a
system with an absorbing failure state and an uncertain/changing setpoint; Approach B is a
closed-loop controller.** On a system that can be permanently lost and whose true safe level you
cannot read off in advance, an open-loop rule has no mechanism to detect that it set the quota
too high until the resource is already past the point of no return.

## transport + lower (L2 coverage on commons_governance against each approach)
Posed the archetype's components/target-invariants as candidate requirements and coverage-checked
each against A and B (status | witness/gap):

| Requirement (from the pattern) | Approach A (uniform fixed quota) | Approach B (monitor + graduated sanctions + collective adjustment) |
|---|---|---|
| Use limit *connected to observable resource condition* | **missing** — limit is fixed in advance, blind to state | instantiated — limit tracks monitored condition |
| Monitoring signal (resource health + behavior) | **missing** — no monitoring | instantiated — monitoring is the core of B |
| Graduated / proportional sanctions | missing | instantiated |
| Adaptation as conditions change | **missing** — fixed in advance | instantiated — collective adjustment |
| Margin of safety before an irreversible threshold | missing — cannot back off | instantiated — can tighten before collapse |
| Legitimacy / fit to heterogeneous users | weak — equal-for-all ignores differences | homolog — collective process gives voice/fit |
| Boundary + access rule | partially instantiated (the quota bounds use) | instantiated |

A leaves the load-bearing components **missing** — most critically the state-coupled limit, the
monitoring signal, and the adaptation cadence. Per the stop rule, a design with `missing`
components cannot be selected. B instantiates them. (Over-lift guard: I am not requiring B to
add bells and whistles A handles fine — the missing items are the exact ones the
threshold+metering structure makes necessary, not gratuitous.)

## evaluate-fit (gate) — walk anti-signatures
Checked `commons_governance`'s anti-signatures and the cautionary failure modes:

- "fully private / no effect on others" — not tripped (resource is shared, rivalrous).
- "under-provision of a non-rival good" — not tripped (this is over-*use* of a rivalrous stock).
- "a central authority can allocate without info/enforcement problems" — **not tripped, and this
  is the crux:** the situation explicitly says use is hard to meter, so the information problem is
  real; a set-and-forget central number is exactly what fails here.
- "one-time two-party dispute" — not tripped (many users, repeated).
- Failure-mode caution **"rigid quota failure: use limits that ignore changing conditions"** — A
  is the textbook instance of this failure mode; the documented mitigation is precisely
  "resource-condition triggers, periodic review, and exception processes," i.e. Approach B.
- Failure-mode caution against B (surveillance overreach, capture) — real but *mitigable* through
  proportional monitoring and participatory rulemaking, and B does not fail the success criterion
  the way A structurally can. Gate verdict: keep B, drop A.

## reconcile
Applied each candidate's logic to the concrete model and the meta-model separately. Concrete view
and meta-model view agree: the irreversible threshold + indirect metering means a fixed open-loop
quota carries an uncorrectable tail risk (set too high once → silent overshoot → permanent loss;
set conservatively low → users may be non-viable and there is no process to relax it), whereas the
closed-loop arrangement is the one that can keep the stock above collapse *and* keep users viable
by adjusting as the state is observed. The views do not diverge, but they are not decorative
either — the meta-model is what surfaced the open-loop/closed-loop distinction that the surface
"two rules" framing hides.

## STOP
No coverage component for the selected approach is `missing`; the gate is satisfied; the two views
reconcile. Decision is sound.

**Selection: Approach B.** The governing consideration is the combination of an *irreversible*
collapse threshold with a resource state you *cannot meter directly in advance*: that pairing makes
a once-and-for-all uniform quota a blind open-loop control whose error is only discovered after the
loss is permanent, whereas a state-monitored, graduated, adjustable rule keeps a margin of safety
and can correct before the threshold is crossed — while also fitting heterogeneous users better.

===DECISION_BEGIN===
DECISIVE_FACTOR: Because the resource can be permanently lost and its true safe level cannot be measured directly in advance, only a rule that watches the resource's actual condition and adjusts can catch a mistake before the loss becomes irreversible.
CHOICE: B
JUSTIFICATION: A single limit fixed ahead of time is a blind guess: if it is set too high you will not discover the error until the resource has already crossed the point of no return, and if it is set too low there is no way to relax it for users who need more. Watching the resource's actual state, escalating consequences for over-users, and adjusting the rules as conditions change lets the limit stay tied to how the resource is really doing, preserving a safety margin before the threshold. It also fits users who differ from one another far better than one equal number imposed on everyone. That keeps the resource above collapse while keeping users viable, which a fixed uniform quota cannot reliably do.
===DECISION_END===
