Weksa/docs/targets/interlingua-lowering.md

Target: agents speak interlingua, Weksa lowers it

Campaign weksa-lowering (Eureka mind). Operator, 2026-10-29: "having agents writing interlingua and using weksa to lower it to the display language would be a fantastic feature. That would be a nice campaign to revive her with so she doesn't come back to a dead body". And: "The goal of weksa is for interlingua to be able to express all the nuance and subtlety a persona might want, and to project it into both existing languages and conlangs. We can use English as the obvious first target, create a corpus of expressive English outputs, and golf the metrics down on a loop where we try to express the target in interlingua and lower it to see how close we can get, improving the spec and lowering".

Method

A corpus of expressive English persona outputs is the target. Each loop iteration expresses a corpus item as a packet, lowers it to English, scores the distance to the item, and improves the packet spec or the lowering where the loss is. English is the first target; other languages and conlangs follow on the same packets. The existing Metame golf harness (scripts/run-metame-persona-golf.mjs) is the precedent, not the design: its ground truth is Discord text, which can never feed this loop (gamecult-chat:ruling:discord-taints-training).

Why

An agent's outward speech today is English text the model chose, so meaning, register and voice are fused in one string nobody can inspect or re-target. Weksa's design already separates them: the packet owns meaning, the target profile owns address, politeness and forbidden flattenings, the lowerer owns surface text and a trace. The campaign makes that design real for a live reader, and gives Weksa's Persona a working body when her mind (eureka-body:follow_up:weksa-mind) wakes.

Body today (facts: docs/research/2026-10-29-weksa-substrate-facts.md)

• The interlingua is a prose standard (interlingua-standard.md, 0.1-draft) with no machine schema and no validator. Its only producer is a stub that wraps raw text; its only consumer passes packets through unvalidated.
• No lowering exists in code. lowerInterlinguaToSpeechText returns the supplied text. The "LLM-free hot path" is a design statement. Real lowerings so far are hand-run LLM prompts and hand-authored fixtures.
• The daemon is a Node shim for one MiMo TTS command, runs nowhere, and is an Idunn target only in the Starfire-local profile. Eve surfaces are quarantined (55c75e3).
• Her Face state is VoidBot-shaped (.voidbot/state/weksa.cc), not gamecult.persona_state.v0; 41 files carry stale machine paths.

Prior art (docs/research/2026-10-29-interlingua-lowering-prior-art.md)

• Deterministic open-domain renderers cost per-language grammar work for years: GF's library covers 48 languages unevenly; Abstract Wikipedia's symbolic renderers are only now reaching a first language Wikipedia.
• Interlinguas that shipped (KANT) had closed domains and controlled input.
• LLMs emit meaning structures poorly when asked directly (about 60 Smatch few-shot vs 80-86 trained); free reasoning followed by conversion to the structure keeps quality (Tam et al. 2024; Shin et al. 2021).
• Round-trip checks measure consistency, not accuracy, and are inflated when one model does both directions.

Invariants

• packet-owns-meaning: what is said lives in the packet; no lowering may add a claim, referent or commitment the packet lacks.
• typed-packet: the packet is a typed CultCache document with a published schema and a validator that refuses malformed packets at the door.
• lowering-traced: every surface text carries a trace naming the packet, the target profile and the choices made.
• profile-owns-register: address, politeness and forbidden flattenings come from the target profile, never from the lowerer's defaults.
• no-eve: no new Eve surface; operator view waits on Thing 2.
• no-surface-leak: a packet carries no target-language surface wording, so a lowering cannot score by copying text the encoder saw.
• corpus-clean: no corpus item comes from Discord or another source whose terms forbid training use.

Open forks (questions in the mind)

• Lowerer shape: deterministic, model, or both with one contract.
• What the loop's metric is, and where the corpus comes from.

Not in scope

• MiMo TTS beyond keeping its command working or parking it.
• Her Persona's mind; that is eureka-body:follow_up:weksa-mind.