whetstone_DSL/docs/constructive_editing_runtime_plan.md

Constructive Editing Runtime Plan (Low-Res)

Objective

Move from MCP contract-level/runtime packet behavior to real constructive editing and code generation execution for representative languages:

• cpp
• rust
• python
• typescript
• javascript
• go
• java
• elisp

Current Baseline

• Sprint 146-155 MCP handlers are now runtimeized and stateful.
• Representative language runtime exists and is wired to tool handlers.
• Handler-level step tests (1703-1795 tool surface set) are passing.
• Taskitem pipeline logging is active and appending LoRA capture records.

Low-Res Plan

1. Runtime to Engine Binding

• Replace synthetic stage outcomes with calls into existing adapter/sync/ regeneration/merge modules.
• Keep current response envelope stable while adding real engine evidence.

2. File Mutation and Replay Integrity

• Add real file-level mutation application paths for constructive step/loop.
• Persist before/after snapshots and replay metadata per operation.

3. Toolchain Execution Integration

• Wire provider routing to real build/test command execution paths.
• Normalize diagnostics from execution output into canonical payloads.

4. Multi-Language Qualification

• Run representative-language deterministic replay and diff checks.
• Gate language tier transitions using real replay/rollback evidence.

5. GA Hardening

• Add end-to-end constructive smoke scenarios per language family.
• Finalize rollout controls and promote only evidence-backed tiers.

6. First-Class Planning Readiness

• Add pre-execution spec readiness scoring and gap detection.
• Synthesize missing constraints/acceptance/environment scaffolds before taskitem generation.
• Gate taskitem execution on minimum planning-readiness thresholds.

Implementation Map

Phase A: Bind Constructive Step to Real Adapter Operations

Primary files:

• editor/src/mcp/RegisterSprint152Tools.h
• editor/src/graduation/RepresentativeLanguageRuntime.h
• editor/src/CppConstructiveEditAdapter.h
• editor/src/RustGoConstructiveEditAdapter.h
• editor/src/PythonTypeScriptConstructiveEditAdapter.h
• editor/src/AdapterOperationUtil.h

Deliverables:

• whetstone_run_constructive_step uses language-specific adapter execution.
• whetstone_get_constructive_status returns real adapter diagnostics.
• whetstone_run_constructive_loop records per-stage real outcomes.

Validation:

• Existing step tests: 1763, 1764, 1765.
• New integration test family: constructive step with real adapter outputs.

Phase B: Real Sync/Regenerate/Merge Path

Primary files:

• editor/src/mcp/RegisterSprint142Tools.h
• editor/src/mcp/RegisterSprint143Tools.h
• editor/src/mcp/RegisterSprint144Tools.h
• editor/src/TextASTSync.h
• editor/src/graduation/CppTextDeltaParserBridgeModel.h
• editor/src/graduation/ConflictRegionDetectorModel.h
• editor/src/graduation/MergePolicyEngineModel.h

Deliverables:

• Sync tools call real text->AST machinery for supported languages.
• Regeneration tools call real AST->text generator path.
• Merge tools emit real conflict regions and policy outcomes.

Validation:

• Existing step tests: 1663-1665, 1673-1675, 1683-1685.
• New cross-language sync/regenerate/merge integration tests.

Phase C: Real Toolchain Provider and Diagnostic Integration

Primary files:

• editor/src/mcp/RegisterSprint151Tools.h
• editor/src/BuildSystem.h
• editor/src/Diagnostics.h
• editor/src/StructuredDiagnostics.h
• editor/src/LspOps.h
• editor/src/graduation/DiagnosticNormalizationCanonicalModel.h

Deliverables:

• whetstone_list_toolchain_providers reflects runtime-detected providers.
• whetstone_probe_toolchain_provider executes probe checks.
• whetstone_normalize_diagnostics ingests raw provider/LSP output.

Validation:

• Existing step tests: 1753, 1754, 1755.
• New tests with representative toolchain output fixtures.

Phase D: Replay/Transaction/GA Evidence from Real Runs

Primary files:

• editor/src/mcp/RegisterSprint153Tools.h
• editor/src/mcp/RegisterSprint154Tools.h
• editor/src/mcp/RegisterSprint155Tools.h
• editor/src/graduation/ConstructiveTransactionSchema.h
• editor/src/graduation/ConstructiveReleaseCertificationPacketModel.h
• editor/src/graduation/MCPReplayDiagnosticsArtifact.h

Deliverables:

• Replay suite compares real run traces.
• Transaction resume/rollback replays actual state transitions.
• GA gate evaluates real determinism and recovery evidence.

Validation:

• Existing step tests: 1773-1775, 1783-1785, 1793-1795.
• New end-to-end replay and rollback scenario tests.

Taskitem Execution Policy for This Plan

• For each implementation phase, generate taskitems using:
  • tools/mcp/run_sprint_taskitem_pipeline.sh <phase_plan_or_sprint_plan.md>
• Export each run:
  • tools/mcp/export_taskitem_run_for_lora.sh <run_output_dir>
• Keep training_data/lora/taskitem_pipeline_runs.jsonl append-only.

Immediate Next Slice

Start Phase A:

• Bind whetstone_run_constructive_step to concrete language adapters.
• Keep fallback path for unsupported operations.
• Add targeted integration tests for cpp, rust, python, typescript.

Parallel planning tranche (active):

• sprint228_plan.md to sprint231_plan.md
• baseline artifacts:
  • logs/taskitem_runs/TEST_ONLY_spec_planning_baseline_20260226/fullstack_spec_readiness.json
  • logs/taskitem_runs/TEST_ONLY_spec_planning_baseline_20260226/deterministic_spec_readiness.json

Planning runtime controls (active):

• sprint232_plan.md to sprint254_plan.md
• semantic bridge + intake augmentation + requirement injection + expansion gating are wired into:
  • tools/mcp/run_sprint_taskitem_pipeline.sh
• current policy default is native-first semantic fallback:
  • WSTONE_SEMANTIC_TASK_EXPANSION_MODE=fallback_only
• fallback diagnostics + remediation metadata are emitted by:
  • tools/mcp/analyze_semantic_fallback_gaps.py
• fallback budget gating is available via:
  • tools/mcp/check_semantic_fallback_budget.py
  • tools/mcp/run_semantic_fallback_budget_gate.sh
• native decomposition quality gate is available in pipeline summary/hard-fail path:
  • native_decomposition_gate
• native reason enrichment can inject semantic tags into native task reasons:
  • WSTONE_NATIVE_REASON_ENRICHMENT
  • native_reason_enrichment
• native decomposition retry path can run second-pass task generation:
  • WSTONE_NATIVE_DECOMP_RETRY
  • WSTONE_NATIVE_DECOMP_TARGET_MIN_TASKS
  • native_decomposition_retry
• impact-specific native decomposition coverage can be enforced:
  • WSTONE_NATIVE_IMPACT_COVERAGE_GATE
  • WSTONE_NATIVE_IMPACT_COVERAGE_ENFORCE
  • WSTONE_NATIVE_IMPACT_COVERAGE_PROFILES
  • native_impact_coverage
• remediation loop can synthesize profile-specific extra constraints and rerun:
  • WSTONE_EXTRA_NORMALIZED_REQUIREMENTS_FILE
  • tools/mcp/synthesize_native_impact_remediation_requirements.py
  • tools/mcp/run_native_impact_remediation_loop.sh
• remediation loop can also synthesize and inject profile-specific task bundles:
  • WSTONE_EXTRA_TASKS_FILE
  • tools/mcp/synthesize_native_impact_remediation_tasks.py
• first-pass pipeline can synthesize profile autofill task bundles without external loop:
  • WSTONE_NATIVE_PROFILE_AUTOFILL
  • WSTONE_NATIVE_PROFILE_AUTOFILL_MAX_TASKS
  • tools/mcp/synthesize_native_profile_autofill_tasks.py
• intrinsic first-pass boost can inject profile-derived decomposition constraints:
  • WSTONE_NATIVE_INTRINSIC_BOOST
  • tools/mcp/synthesize_native_intrinsic_boost_requirements.py
• intrinsic multishot generator path can run profile-targeted decomposition passes:
  • WSTONE_NATIVE_MULTISHOT_DECOMP
  • WSTONE_NATIVE_MULTISHOT_MAX_PROFILES
  • WSTONE_NATIVE_MULTISHOT_APPLY_MODE
  • native_multishot
• single-shot profile shaping path can close profile coverage without multishot:
  • WSTONE_NATIVE_SINGLESHOT_PROFILE_SHAPE
  • tools/mcp/synthesize_single_shot_profile_shape_tasks.py
  • native_single_shot_profile_shape
• raw-only candidate search (no overlays) can benchmark intrinsic generator variants:
  • WSTONE_NATIVE_RAW_CANDIDATE_SEARCH
  • WSTONE_NATIVE_RAW_CANDIDATE_MAX_VARIANTS
  • WSTONE_NATIVE_RAW_CANDIDATE_REQUIRE_UPLIFT
  • tools/mcp/score_native_tasks_profile_coverage.py
• closure ladder can select the minimal passing strategy automatically:
  • tools/mcp/run_native_profile_closure_ladder.sh
• closure ladder can route around historically ineffective raw-only mode:
  • tools/mcp/analyze_raw_candidate_uplift_history.py
  • WSTONE_CLOSURE_LADDER_SKIP_RAW_WHEN_NO_UPLIFT
• closure ladder outcomes can be aggregated in batch:
  • tools/mcp/run_native_profile_closure_ladder_batch.sh
  • tools/mcp/analyze_closure_ladder_outcomes.py
• raw gap backlog can be synthesized from ladder raw-only attempts:
  • tools/mcp/synthesize_raw_gap_backlog.py
• raw top-gap hardening can patch weak native outputs before overlay stages:
  • tools/mcp/harden_native_tasks_top_gaps.py
  • WSTONE_NATIVE_RAW_HARDEN_TOP_GAPS
  • native_raw_hardening
• raw candidate selection can be weighted by historical gap priorities:
  • WSTONE_NATIVE_RAW_TOP_GAP_WEIGHTED_SELECT
  • WSTONE_NATIVE_RAW_TOP_GAP_BACKLOG_FILE
  • scorer --top-gaps telemetry (top_gap_score)
• raw candidate search can enforce top-gap uplift as hard policy:
  • WSTONE_NATIVE_RAW_TOP_GAP_REQUIRE_UPLIFT
  • failure code 18 when no weighted uplift is achieved
• raw candidate generation can ingest backlog-driven top-gap normalized requirements:
  • tools/mcp/synthesize_raw_top_gap_requirements.py
  • WSTONE_NATIVE_RAW_TOP_GAP_REQUIREMENTS
  • WSTONE_NATIVE_RAW_TOP_GAP_MAX_SIGNALS
  • native_raw_top_gap_requirements
• raw candidate search can run adaptive retry with expanded top-gap requirements:
  • WSTONE_NATIVE_RAW_TOP_GAP_ADAPTIVE_RETRY
  • WSTONE_NATIVE_RAW_TOP_GAP_RETRY_SIGNALS
  • native_raw_adaptive_retry
• raw candidate search can expand intrinsic exploration with signal-targeted variants:
  • tools/mcp/synthesize_raw_signal_targeted_variants.py
  • WSTONE_NATIVE_RAW_SIGNAL_TARGETED_VARIANTS
  • WSTONE_NATIVE_RAW_SIGNAL_TARGETED_MAX_VARIANTS
  • native_raw_signal_targeted_variants
• raw candidate generation can inject intrinsic prompt-pack constraints from gap signals:
  • tools/mcp/synthesize_raw_intrinsic_prompt_pack.py
  • WSTONE_NATIVE_RAW_INTRINSIC_PROMPT_PACK
  • WSTONE_NATIVE_RAW_INTRINSIC_PROMPT_MAX_SIGNALS
  • native_raw_intrinsic_prompt_pack
• raw candidate generation can inject explicit output-shape template controls:
  • tools/mcp/synthesize_raw_template_control_pack.py
  • WSTONE_NATIVE_RAW_TEMPLATE_CONTROL_PACK
  • WSTONE_NATIVE_RAW_TEMPLATE_CONTROL_MAX_SIGNALS
  • native_raw_template_control_pack
• raw candidate scoring can evaluate deterministic structural projections pre-score:
  • tools/mcp/project_raw_candidate_structure.py
  • WSTONE_NATIVE_RAW_STRUCTURAL_PROJECTOR
  • native_raw_structural_projector
• raw candidate selection now persists selected tasks into generation artifacts for gate parity:
  • keeps native_raw_candidate_search and native_impact_coverage on the same task set
• raw score/gate parity can be emitted and hard-enforced:
  • native_raw_score_gate_parity
  • WSTONE_NATIVE_RAW_SCORE_GATE_PARITY_ENFORCE