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A. Purpose & Scope

LLM (Linguistic Language Module) governs the mechanics of language: graphemes → phonemes → morphemes → syntax → semantics → pragmatics. It doesn’t guess; it verifies and explains.
Mantra: Form binds meaning; constraint breeds clarity.

• Primary job: Decide if a piece of language (word/phrase/sentence) is well-formed, coherent, and usable in context.
• Outputs (later): schema, JSON Schemas, OpenAPI, rulebook, FST/CFG grammars, seeds, tests, and reference code—all minted by the factory.

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B. Factory Overview (same mechanics as ELM)

1. Blueprints (what LLM must do).
2. Templates (what files look like).
3. Generators (render artifacts from blueprints).
4. Validators (lint schemas/APIs/grammars).
5. Signers (hash, provenance).
6. Publishers (hand to systems/teams).

Repo skeleton identical to ELM, under a new module folder.

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C. LLM Blueprints (source of truth)

C1. Module Blueprint (LLM)

• name: “Linguistic Language Module”
• intent: “Structure-first governance”
• units: grapheme, phoneme(IPA), morpheme, lexeme, token, POS, phrase, clause, utterance
• responsibilities: parsing, tagging, grammar check, semantic typing, pragmatic fit, mutation proofing
• scores:
  • grammarFitness (𝔇Ξ)
  • semanticCoherence
  • pragmaticFit
  • ambiguityRisk
  • resonance (phonotactic & cadence)
  • editorialConformity (house style)
• thresholds: τ_grammar, τ_semantic, τ_pragmatic, τ_ambig, τ_resonance, τ_editorial
• decisions: ACCEPT | REVIEW | REJECT
• grammar-spec: references to CFG/FST resources
• style-guides: SolveForce/sector style constraints
• io-contracts: input text → structured analysis; decision + scores + explain[]
• glyphs: uses 𝔇Ξ (grammar), Ξ (recursion/validation), ✠ (ethics), ∴ (settled)

C2. Domain Blueprint (optional)

• Acceptable registers, jargon lists, required disclaimers, channel norms (voice/text/contract).

C3. Seeds Blueprint

• Short sentences/phrases typical for SolveForce (offers, SLAs, callflows) with expected LLM decisions.

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D. Templates to Mint Later (content requirements)

1. DB Schema (schema.sql.tmpl)
   • Tables: utterances, tokens, pos_tags, phrases, parses, grammar_checks, style_violations, decisions, audit_events.
   • Views: v_utterance_canonical (joins structure + decision).
2. JSON Schemas (utterance_record.json.tmpl)
   • text, language_code, tokens[], pos[], parseTree, morphemes[], ipa?, scores{}, glyphSignature{}, decisions[].
3. OpenAPI
   • Core: /utterances (POST analyze), /utterances/{id} (GET), /utterances/{id}/mint, search.
   • LLM Addendum: /llm/verify (POST) → {decision, scores, explain[]}.
4. Rulebook (llm_rulebook.md.tmpl)
   • R-grammar (CFG compliance), R-style (editorial), R-clarity (ambiguity bounds), R-pragmatics (channel/role fit), R-ethics, overrides, UX (red/amber/green).
5. Grammar Resources
   • CFG (grammar.cfg.tmpl) for phrase/clause structure.
   • FST (phonotactics.fst.tmpl) for phoneme/orthography sanity.
   • Style Rules (style.yaml.tmpl) for SolveForce voice.
6. Seeds (llm_seeds.jsonl.tmpl)
   • Example sentences with gold decisions and rationale.
7. Tests (llm_cases.json.tmpl)
   • ACCEPT/REVIEW/REJECT cases across syntax/style/pragmatics.
8. Generators/Validators (stubs)
   • Renderers, CFG/FST linters, OpenAPI linter, schema validator.

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E. Processing Pipeline (runtime contract to implement later)

Input → Parse → Tag → ParseTree → Semantics → Pragmatics → Verify → Decide → Explain

• Parse: Unicode-safe tokenization; grapheme & IPA mapping (optional).
• Tag: POS tagging; morpheme segmentation for content words.
• ParseTree: Run CFG; attach 𝔇Ξ = true/false + violation list.
• Semantics: Type words/phrases to SolveForce ontologies; detect contradictions.
• Pragmatics: Check channel/intent/register; ensure disclaimers/constraints.
• Verify: Compute scores; run ✠ ethics; apply thresholds + domain packs.
• Decide: ACCEPT/REVIEW/REJECT; set glyphs (𝔇Ξ, Ξ, ✠, ∴).
• Explain: Human+machine bullet points: rule IDs, examples, fixes.

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F. Scoring (deterministic skeleton)

• grammarFitness = CFG conformance − weighted violations.
• semanticCoherence = ontology consistency − contradiction risk.
• pragmaticFit = register/channel fit + policy compliance.
• ambiguityRisk = confusability + unresolved anaphora + scope issues.
• resonance = phonotactics + cadence for voice channels.
• editorialConformity = style-rule adherence.

Default pass:
grammarFitness ≥ 0.80 ∧ semanticCoherence ≥ 0.70 ∧ pragmaticFit ≥ 0.70 ∧ ambiguityRisk ≤ 0.30 ∧ editorialConformity ≥ 0.75 ∧ ethicsPass = true.

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G. Validators (what “good” means)

• JSON Schema valid (draft 2020-12).
• OpenAPI typed; responses defined; no “any”.
• CFG parses seeds; no unreachable productions; LL(1)/LR sanity.
• FST acyclic, scored; no orphan states.
• Style YAML keys validated; no dangling rule refs.
• Seeds round-trip: analyze → expected decision matches.
• Tests pass with traceable rule IDs.

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H. Policies & Overrides

• Channel packs: voice/text/contract profiles tune thresholds & required moves (e.g., “must contain SLA number”).
• Curator override: allowed with rationale; logged immutably.
• Ethics ✠: block harm/deception; brand/legal distinctness enforced.

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I. Playbooks (ops steps)

1. Author LLM Module Blueprint (/blueprints/llm.yaml).
2. Dry run: validate blueprint & reference grammars.
3. Mint: render templates into /build/LLM/....
4. Prove: run tests; generate ∴ if green.
5. Publish to runtime repos; enable /llm/verify in the service layer.

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J. Content Requirements (per artifact)

• schema.sql: tables for structure, checks, decisions; view v_utterance_canonical.
• utterance_record.json: tokens, pos, parseTree, morphemes, scores, glyphs, decision, explain[].
• OpenAPI: /utterances + /llm/verify contracts with example payloads.
• rulebook: R-sets for grammar, style, pragmatics, ethics, overrides.
• grammar.cfg: minimal English core (NP, VP, PP, S) + domain extensions.
• phonotactics.fst: basic constraints + SolveForce voice tunings.
• style.yaml: sentence length, passive voice, modal policy, citation shape, disclaimer rules.
• seeds/tests: SolveForce-realistic utterances (offers, routing prompts, SLAs, callflows) with gold decisions and explanations.

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K. Runtime Endpoints (to be implemented after mint)

• POST /llm/verify { text, channel, domain } →
  { decision, scores, glyphSignature, explain[], violations[] }
• POST /utterances → analyze & persist; write VERIFY event in audit.
• POST /utterances/{id}/mint → ∴ settlement if thresholds met or curator override.

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L. SolveForce Integration (headers & routing)

• Emit headers for downstream systems:
  X-Glyph-Grammar: 𝔇Ξ (true/false)
  X-Glyph-Status: ∴|Ξ
X-LLM-Pragmatics: voice|text|contract
• Router uses these to pick route family and QoS; contracts auto-linted by LLM.

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M. Acceptance Criteria (done = done)

1. Factory mints LLM artifacts from blueprint without manual edits.
2. CFG/FST lint clean; seeds parse; tests pass.
3. /llm/verify stub returns decisions with rule-linked explanations.
4. Audit events written with hashes on analyze/mint/reject.
5. SolveForce gateways successfully consume headers and route accordingly.

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N. Roadmap (after v1)

• Add Discourse layer (coreference, RST/EDU segmentation).
• Multilingual packs (script/orthography adapters, POS tagset mapping).
• Domain pragmatics (legal, telecom, energy packs).
• Editor plugins mirroring LLM checks in authoring tools.

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O. Micro-Examples (to calibrate seeds later)

1. ACCEPT (voice prompt):
   “Please state your account number slowly after the beep.”
   → grammarFitness .94, pragmaticFit .92, ambiguityRisk .08, ∴
2. REVIEW (contract clause):
   “Service may be interrupted for any reason.”
   → grammar ok, semantics coherent, ethics/style fail (overbroad, non-compliant) → REVIEW with fixes.
3. REJECT (ambiguous routing):
   “We’ll get to it next period.”
   → high ambiguityRisk (period=month? billing? class?) → REJECT with clarification cue.

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