Complete Phase 15 spoken-word module

docs/rewrite-notes.md

@@ -68,6 +68,10 @@ Implemented:
 - Production homophones module package with Python-aligned prompt intent and guardrails.
 - Explicit `--modules homophones` runtime path through runner, shared proposal generation, validators, application, reporting, and diagnostics.
 - Focused multi-module runtime tests for already-implemented interoperability (for example `glossary,homophones`) without claiming full default-pipeline completion.
+- Production spoken_word module package with Python-aligned prompt intent and guardrails.
+- Explicit `--modules spoken_word` runtime path through runner, shared proposal generation, validators, application, reporting, and diagnostics.
+- Focused multi-module runtime tests for already-implemented interoperability (for example `spoken_word,grammar`) without claiming full default-pipeline completion.
+- All production modules now exist (`glossary`, `homophones`, `spoken_word`, `grammar`), but default full-sequence integration remains Phase 16 work.
 - Broad deterministic and CLI/subprocess test coverage for implemented phases through `go test ./...`.
 - Internal typed structured LLM contract (`StructuredLLMClient.CompleteStructured(ctx, req, out)`).
 - `internal/framework/llm` instructor-go-backed adapter with:
@@ -83,8 +87,6 @@ Implemented:
 - Generic JSON diagnostics primitives for LLM interactions (request metadata, request payload, response payload, optional error payload) with secret redaction.
 
 Not yet implemented in runtime pipeline:
-- Real correction module for `spoken_word`.
-- Domain proposal prompts for remaining real module.
 - End-to-end transcript polishing behavior with the full default module sequence.
 
 ## Completed phases
@@ -223,7 +225,7 @@ Not implemented in Phase 8 (by design):
 
 ## Remaining work plan
 
-Next recommended phase: **Phase 15 (spoken-word module)**.
+Next recommended phase: **Phase 16 (default full pipeline integration)**.
 
 ## Phase 9: Structured LLM client and scheduler infrastructure
 
@@ -418,41 +420,29 @@ Not implemented in Phase 14 (by design):
 
 ## Phase 15: Spoken-word module
 
-### Purpose
+Completed.
 
-Implement conservative dysfluency cleanup while preserving substantive meaning.
+Implemented:
+- Production spoken_word module package in `internal/modules/spoken_word`.
+- Spoken_word prompt builder aligned to Python intent and constrained to conservative dysfluency cleanup.
+- Prompt context using glossary/protected-term information (names, aliases, plurals where present) to avoid damaging known domain terms.
+- Strong prompt guardrails preserving meaning, intent, speaker voice, named entities, game/domain terms, and substantive content.
+- Explicit prompt guardrails against summarization, style rewriting, grammar-only cleanup, punctuation-only cleanup, invention, event reordering, and certainty inflation.
+- Spoken_word proposal generation through shared `internal/framework/proposal_generation` using `contracts.StructuredLLMClient`.
+- Scheduler-aware spoken_word proposal generation through existing scheduler hooks.
+- Spoken_word replacement policy `require_unique` (matching Python behavior).
+- Spoken_word validator chain using existing deterministic and LLM-backed validators.
+- Strong semantic guardrails in runtime validator chain through existing LLM-backed validators (`spoken_word_review`, `meaning_reversal_review`).
+- Spoken-word confidence threshold enforcement through existing config + confidence-threshold validator behavior.
+- Protected-term guardrails remaining active for spoken_word via existing deterministic validators.
+- Explicit runtime support for `--modules spoken_word` through normalization, chunking, runner, proposal generation, validation, application, and reporting.
+- Prompt/response diagnostics artifacts for spoken_word proposal + validator interactions with secret redaction.
+- Module-level reports for spoken_word including generated proposals, validator decisions/rejections, applied changes, and application skips.
+- CLI/runtime fake-client tests for approved cleanup, validator rejection, meaning-changing rejection, application skips, diagnostics, protected-term rejection behavior, failure/error.log behavior, and report outputs (`--report-json` and run-dir `report.json`).
+- Focused interoperability tests for already-implemented module combinations (for example `spoken_word,grammar`) to verify working-transcript handoff and guardrails without claiming full default-sequence parity.
 
-### Scope
-
-Implement:
-- `spoken_word` module package.
-- Spoken-word prompt builder ported from Python.
-- Spoken-word structured response model.
-- Spoken-word replacement policy.
-- Spoken-word confidence threshold handling.
-- Spoken-word validator chain.
-- Strong semantic guardrails using LLM-backed validators.
-- Prompt/response diagnostics.
-- CLI support for `--modules spoken_word`.
-- Fake LLM tests.
-- Tests for rejection of meaning-changing cleanup.
-
-Do not implement:
-- Prompt redesign beyond faithful porting.
-- New stylistic rewriting behavior not present in the Python implementation.
-
-### Expected behavior at end of phase
-
-Running `audita process ... --modules spoken_word` should perform real conservative dysfluency cleanup, with guardrails against semantic changes.
-
-### Definition of done
-
-- Spoken-word module runs in the production runner.
-- Spoken-word proposals are generated through structured LLM calls.
-- Semantic validators reject meaning-changing proposals.
-- Applied/skipped spoken-word changes appear in reports.
-- Prompt/response diagnostics are written.
-- `go test ./...` passes without requiring external LLM credentials.
+Not implemented in Phase 15 (by design):
+- Full default module sequence execution as a feature-complete claim.
 
 ## Phase 16: Default full pipeline integration