derive-prompt-is-deterministic-and-reproducible
IN derived (depth 2)
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.
Summary
When the derive pipeline builds prompts for its agents, the results are fully repeatable. The same seed always selects the same subset of beliefs, and the token budget is split the same way each time, so running derive twice with the same inputs produces identical prompts — useful for debugging and testing.
Justifications
SL — Deterministic sampling plus accurate budgets yield reproducible derive prompts
Antecedents (all must be IN):
- sample-mode-is-deterministic — `_build_beliefs_section` with `sample=True` and a fixed `seed` produces identical output across calls, enabling reproducible derive prompts
- derive-budget-allocation-is-accurate — The derive pipeline's proportional belief-budget allocation produces correct per-agent token counts
Dependents
These beliefs depend on this one:
- cluster-derive-is-semantically-informed-and-deterministic — 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).
- derive-achieves-flexibility-with-reproducibility — The derive pipeline resolves the tension between strategic flexibility and deterministic reproducibility: three budget strategies (alphabetical truncation, random sampling, semantic clustering) provide diverse exploration approaches, while fixed-seed deterministic sampling and accurate proportional allocation ensure each strategy produces identical results across runs.
- derive-pipeline-achieves-end-to-end-fault-tolerance — The derive pipeline achieves end-to-end fault tolerance through three independent layers: proactive defense (fail-soft validation, Jaccard retraction guards, environment isolation), reactive resilience (partial results persisted via JSON reports after each round, error states signaled through return codes), and prompt reproducibility (deterministic sampling with fixed seeds enables consistent re-runs after failures).
- derive-pipeline-is-reproducible-and-defense-in-depth — The derive pipeline achieves both reproducibility (deterministic sampling with fixed seeds and accurate budget allocation) and defense-in-depth at the application stage (validation-before-apply trust boundary with per-proposal error isolation), ensuring pipeline runs are repeatable and any surviving bad proposal cannot corrupt sibling proposals.