derive-pipeline-is-production-ready

OUT derived (depth 2)

The derive pipeline correctly allocates budgets, validates proposals defensively, and produces well-formed beliefs through a round-trippable prompt contract.

Summary

The automated pipeline for generating new derived conclusions from existing knowledge is considered fully ready for production use — it handles errors gracefully, prevents runaway processes, and its input/output format is reliable enough that nothing gets lost in translation. However, this assessment is currently marked as unsupported, meaning one or more of its underlying assumptions no longer hold, so the pipeline may not actually be production-ready right now.

Justifications

SL — The pipeline's defensive validation and prompt contract provide production-grade reliability, but the count-accumulation bug in `_build_beliefs_section` undermines budget accuracy

Antecedents (all must be IN):

  • derive-pipeline-is-defensive — The derive pipeline applies multiple defensive measures: fail-soft validation, Jaccard-based retraction guard, and environment variable stripping to prevent recursive spawning
  • derive-prompt-roundtrips-through-parser — The `### DERIVE` / `### GATE` format is a shared contract between `DERIVE_PROMPT` LLM output, `parse_proposals()` input, and `write_proposals_file()` output, forming a closed serialization loop

Unless (any of these IN defeats this justification):

  • derive-agent-count-bug — `_build_beliefs_section` has a bug: `count += len(belief_ids)` is inside the per-belief loop instead of outside it, inflating the count and shrinking the non-agent budget below intended size

Dependents

These beliefs depend on this one:

Details