You are solving a hard design problem. You have access to a reference catalog of cross-domain abstractions through the encyclopedia tools. Retrieval is SEMANTIC, type-aware, and neighborhood-aware:
- search_prime(query): query it with the domain-stripped META-MODEL of the problem (the abstract structure, NO domain words), not the raw problem text — cross-domain retrieval is far better that way. Hits carry a structural/framed label, a distinctiveness band, and (for crowded hits) a near-synonym family.
- search_by_facets(facets=[...]): for OBLIQUE problems that instantiate several structures at once, pass a LIST of short domain-stripped facet phrases (one per structural aspect) and READ THE PER-FACET lists — this surfaces latent patterns that a single blended query buries.
- get_prime / get_archetype: full records (structural signature, components, anti-signatures).
- get_prime_neighborhood(slug): a prime's typed-graph neighbors. find_archetypes_for_prime, find_related_primes, list_components, find_archetypes_using_component, search_archetype, corpus_stats.

Solve it by executing this NINE-STEP procedure IN ORDER, exactly once each, WITHOUT returning to a previous
step (this fixed order is the method under test — follow it even if you would prefer to reorder or repeat):
 1. Specify the problem statement (decision, bounds, success/failure criteria).
 2. Identify the operative prime abstractions present (search_prime / get_prime; err toward inclusion).
 3. Salience-rank the primes by load-bearing relevance.
 4. Prune to an operative subset (~3-9) with rationale.
 5. Build a context-specific model: an explicit typed relational structure (entities/actors as nodes,
    relationships as labeled edges, primes annotated on it).
 6. Construct a meta-model: strip domain specifics, keep the structural skeleton.
 7. Query solution archetypes whose source primes match (find_archetypes_for_prime, get_archetype;
    search_archetype as fallback).
 8. Reason via both views: apply candidate archetypes' action logic to the context model and the meta-model;
    reconcile.
 9. Evaluate fit and produce the recommendation: walk each candidate's anti-signatures / trigger conditions;
    drop archetypes the scenario trips; output the final design.

PROBLEM.
A coastal fishery harvesting a single demersal stock has shown three years of declining catch-per-unit-effort and shrinking average fish size. The biologist's stock assessment estimates that current harvest exceeds maximum sustainable yield (MSY) by ~20% and that, on the current trajectory, the stock will cross a recruitment-collapse threshold within 4-7 years. The fishery is open-access in practice (no enforced individual quotas); ~120 small-boat operators across 5 villages depend on it for income, with fish-processing buyers downstream. A regulator has authority to set total allowable catch but has historically deferred to the industry.

Decision required: What intervention design preserves the stock without destroying the livelihoods that depend on it?

Success criteria: Stock biomass returns to MSY-supporting range within 10 years AND <20% drop in aggregate fisher income (averaged across the cohort, not per-boat). Failure = stock collapse OR a regulatory regime that pushes the bottom quartile of operators below subsistence.

OUTPUT — write your FINAL RECOMMENDATION as plain prose, MAX 1000 words, inside a fenced block exactly:
===RECOMMENDATION_BEGIN===
<the design: concrete mechanisms, rules, thresholds, paths, and a final operating rule>
===RECOMMENDATION_END===
Rules for the recommendation text: write integrated prose, NOT a numbered checklist mirroring any
requirements/steps, and do NOT label sections with requirement numbers; use plain domain terms only; do NOT
name or allude to any external catalog, framework, methodology, named discipline, prime, archetype, or to
this exercise/method; if a candidate requirement does not genuinely fit the problem, leave it out rather than
forcing it. Above the recommendation block, include your working (state + the verbs/steps you ran, with a
rough token/operation note at the very end as `COST: ~<n> operations, ~<n> tokens`); the working is discarded
before grading. Write your ENTIRE response to: experiments/project02_engine_2026-05-25/outputs/c08.md
