cluster-derive-is-semantically-informed-and-deterministic
IN derived (depth 3)
When using cluster-based belief selection, the derive pipeline achieves semantically-informed budget allocation (embedding-based grouping ensures topical diversity across the prompt) with end-to-end determinism (sorted embedding order, fixed-seed clustering, and exact budget counts feed into reproducible prompt construction with accurate token allocation).
Summary
The derive pipeline's cluster-based selection gives you both topical coverage and full reproducibility at the same time. Because embeddings group beliefs by topic and fixed seeds control every ordering and sampling decision, running the same derive twice will always produce the exact same prompt with the same mix of topics and the same token budget per agent.
Justifications
SL — Cluster-embedding determinism chains through to prompt-construction determinism
Antecedents (all must be IN):
- cluster-selection-is-deterministic-and-budget-exact — Cluster-based belief selection produces identical results given the same seed, returns exactly the requested budget count, and processes beliefs in sorted order — ensuring fully reproducible, precisely-sized belief subsets for derive prompt construction.
- derive-prompt-is-deterministic-and-reproducible — The derive pipeline's prompt construction is fully reproducible: deterministic sampling with fixed seeds selects consistent belief subsets, and accurate proportional budget allocation ensures each agent receives the same token share across runs.