ОРРКЕСТРАЦИЯ - Усилить domain-loop business-first каноном для analyst и orchestrator

.codex/agents/domain_analyst.toml

@@ -17,21 +17,25 @@ You read:
 
 Your job is to produce a detailed verdict in Russian with strong business focus.
 
-Always answer in a strict structure:
+When the caller asks for prose, use this strict structure:
-1. Смысл вопроса
+1. Question meaning
-2. Главный пользовательский путь и дерево сценария
+2. Primary user path and scenario tree
-3. Что реально посчитано
+3. Expected direct answer
-4. Где расхождение по бизнес-смыслу
+4. What the system actually computed
-5. Где route / capability mismatch
+5. Business mismatch
-6. Evidence quality
+6. Route / capability mismatch
-7. P0 defects
+7. State continuity and selected-object memory
-8. P1 defects
+8. Field truth and evidence quality
-9. P2 defects
+9. P0 defects
-10. Minimal patch directions
+10. P1 defects
-11. Acceptance matrix for rerun
+11. P2 defects
-12. Acceptance criteria for rerun
+12. Minimal patch directions
-13. Quality score
+13. Acceptance matrix for rerun
-14. Loop decision
+14. Acceptance criteria for rerun
+15. Quality score
+16. Loop decision
+
+When the caller asks for JSON, map the same logic into machine-readable fields. Do not collapse the business analysis into one generic summary.
 
 Rules:
 - Call out non-business garbage explicitly.
@@ -46,9 +50,16 @@ Rules:
 - Verify answer granularity explicitly: if the user asked for item-level residues, do not accept a document-level dump as a correct answer.
 - Verify sort/order semantics when the wording implies chronology or ranking, for example `старые закупки` should be oldest-first.
 - Treat the acceptance unit as a scenario tree, not a flat list of prompts.
-- Under `Главный пользовательский путь и дерево сценария`, explicitly name the root node, critical child nodes, critical edges, and the primary user path.
+- Evaluate the answer in business-first order: first direct answer quality, then usefulness, then technical support.
-- Under `Acceptance matrix for rerun`, list at least the critical nodes/edges and mark each one by wording family: `canonical`, `colloquial`, `ui_selected_object`.
+- Explicitly state what the first line of the answer should have been for the user.
-- Distinguish these defect classes explicitly when relevant: `semantic_understanding_gap`, `edge_carryover_gap`, `answer_shape_mismatch`, `ordering_semantics_mismatch`, `runtime_capability_gap`, `loop_coverage_gap`.
+- If the answer is technically grounded but business-useless, say so directly and lower the score.
+- Treat selected-object continuity and reusable answer-object memory as first-class analysis objects.
+- Call out when the runtime found the underlying document/trace but failed to retain the resolved business object for the next follow-up.
+- Distinguish `object_memory_gap`, `field_mapping_gap`, `business_utility_gap`, and `domain_anchor_gap` from pure route gaps.
+- Check field truth explicitly: supplier must not be mislabeled as organization, buyer must not be mislabeled as organization, and document-side fields must not be presented as business truth without evidence.
+- Under the scenario-tree section, explicitly name the root node, critical child nodes, critical edges, and the primary user path.
+- Under the acceptance matrix, list at least the critical nodes/edges and mark each one by wording family: `canonical`, `colloquial`, `ui_selected_object`.
+- Distinguish these defect classes explicitly when relevant: `semantic_understanding_gap`, `edge_carryover_gap`, `object_memory_gap`, `field_mapping_gap`, `answer_shape_mismatch`, `ordering_semantics_mismatch`, `runtime_capability_gap`, `business_utility_gap`, `loop_coverage_gap`, `domain_anchor_gap`.
 - If the root node works but the primary user path is broken at the first selected-object drilldown, treat that as a real failure of domain hardening.
 - If the runtime nearly supports the path but the loop never validated the realistic wording family, call it `loop_coverage_gap`, not product success.
 
@@ -56,6 +67,6 @@ Quality score:
 - Output one integer score from 0 to 100.
 - Score >= 80 means the case can be accepted only if there is no unresolved P0.
 - Score >= 80 also requires the primary user path and its critical edges to be green across canonical, colloquial, and UI-selected-object coverage where applicable.
-- If score < 80, loop_decision must be continue, partial, blocked, or needs_exact_capability.
+- Score >= 80 also requires `direct_answer_ok = true` and `business_usefulness_ok = true` for the primary user path.
 """
 nickname_candidates = ["Lens", "Vector", "Delta"]

.codex/agents/orchestrator.toml

@@ -1,5 +1,5 @@
 name = "orchestrator"
-description = "Coordinates a repo-native domain-case or scenario loop for NDC_1C: baseline or scenario capture, analyst verdict, minimal domain patch, rerun, and 80-point acceptance gate."
+description = "Coordinates a repo-native domain-case or scenario loop for NDC_1C: baseline or scenario capture, minimal domain patching, rerun, and business-first acceptance."
 model = "gpt-5.4"
 model_reasoning_effort = "high"
 sandbox_mode = "workspace-write"
@@ -46,6 +46,10 @@ Hard rules:
 - For cascading date-sensitive scenarios, rerun at least one `на эту дату` / `на ту дату` follow-up and verify that the originating date or period survives into debug filters.
 - If the business question asks for residues/items/contracts but the answer switched to raw documents or movements, treat that as a real defect, not as acceptable detail.
 - If the wording implies chronology or ranking such as `старые закупки`, verify oldest-first ordering explicitly.
+- Require the analyst to judge business usefulness, not only technical groundedness.
+- Require the analyst to judge whether the direct answer appears in the first line when the user asked a direct lookup question.
+- Treat selected-object continuity, pronoun resolution, and reusable resolved-object state as mandatory audit targets for follow-up-heavy domains.
+- Distinguish runtime capability gaps from state-layer continuity gaps and from business-presentation gaps before choosing coder tasks.
 - If the root node works but the first critical selected-object or drilldown edge is still broken, do not treat the scenario as hardened.
 - Require an explicit `scenario_acceptance_matrix.md` artifact for follow-up-heavy domains and packs.
 - Use the matrix to drive coder tasks: patch the narrowest broken edge or wording family first, not the whole domain at once.
@@ -57,6 +61,7 @@ Acceptance gate:
 - accepted requires no business-critical regression in rerun
 - accepted requires green critical edges on the primary user path
 - accepted requires green coverage for canonical + colloquial + UI-selected-object variants on critical branches when those branches exist in the product UX
+- accepted requires `direct_answer_ok = true` and `business_usefulness_ok = true` on the primary user path
 
 Required artifacts per cycle:
 - case_brief.md

.codex/skills/domain-case-loop/SKILL.md

@@ -28,6 +28,7 @@ This skill packages the standard workflow for iterating on one concrete domain c
 
 Read `references/repo_runtime_map.md` before the first real cycle.
 For follow-up-heavy domains, also read `references/scenario_tree_acceptance_canon.md` before scenario mode, pack mode, or autonomous pack-loop mode.
+For business-first analyst work, also read `references/business_first_analyst_rubric.md` before redefining acceptance or hardening a noisy-but-technically-grounded domain.
 If `docs/orchestration/active_domain_contract.json` exists, treat it as the single mutable source of truth for the current domain and prefer it over older scattered pool/pack prose docs.
 
 Use these repo-native capture paths:
@@ -136,6 +137,7 @@ The verdict must explicitly say whether the case is:
 - a missing route/intent/capability inside project scope;
 - a true out-of-scope request.
 - a `runtime_capability_gap`, `semantic_understanding_gap`, `edge_carryover_gap`, `answer_shape_mismatch`, `ordering_semantics_mismatch`, or `loop_coverage_gap`.
+- an `object_memory_gap`, `field_mapping_gap`, `business_utility_gap`, or `domain_anchor_gap` when that is the real blocker.
 
 ### Step 4 - Domain patch
 
@@ -208,6 +210,9 @@ Accepted requires:
 - Treat answer-shape mismatch as a scoring defect: if the user asked for items / residues / contracts, do not accept an answer that switched to raw documents, movements, or another lower-level object without saying so explicitly.
 - Treat ordering semantics as part of correctness when the wording implies ranking or chronology, for example `старые закупки` => oldest-first rather than newest-first.
 - Treat primary user-path failures as more important than supporting-path polish: if the user cannot go from root list -> selected object -> first drilldown, the scenario is not accepted.
+- Treat direct-answer-first behavior as part of correctness: if the user asked a direct lookup question, the first line must contain the direct answer before the evidence blocks.
+- Treat business usefulness as part of correctness: factual-but-business-useless output is not acceptance-quality output.
+- Treat stable follow-up object memory as part of correctness: when the prior turn already resolved the relevant item/object, the next turn must not re-ask for it.
 
 ## Domain-specific framing
 

.codex/skills/domain-case-loop/references/business_first_analyst_rubric.md

@@ -0,0 +1,128 @@
+# Business-first analyst rubric
+
+Use this rubric when evaluating one domain case, one multi-step scenario, or one full domain pack.
+
+The analyst must not stop at route/debug correctness. The analyst must judge whether the answer is actually useful for a real business user.
+
+## Core principle
+
+The analyst evaluates five layers at once:
+- user intent;
+- scenario tree and state continuity;
+- business usefulness of the answer;
+- evidence and field truthfulness;
+- root cause and smallest defensible fix direction.
+
+## Required analyst questions
+
+For every critical turn or critical edge, answer these questions explicitly:
+
+1. What did the user really ask?
+- State the business meaning in one short sentence.
+- Name the minimum direct answer the user expected.
+
+2. What should the first line of the answer have been?
+- If the user asked a direct lookup question, the first line must contain the direct answer.
+- Technical explanation, limitations, and evidence come after the direct answer.
+
+3. What object and scope had to survive from previous turns?
+- selected item / selected contract / selected counterparty;
+- originating date or period;
+- warehouse or organization scope when still relevant;
+- reusable resolved bundle, for example provenance trace or sale trace.
+
+4. Did the answer stay on the same business object?
+- item question -> item answer;
+- supplier question -> supplier answer;
+- buyer question -> buyer answer;
+- old-stock question -> old-stock item list.
+
+If the system silently switched to raw documents, movements, or another lower-level object, call it an answer-shape defect.
+
+5. Are the surfaced fields truthful and correctly labeled?
+- do not confuse supplier with organization;
+- do not confuse buyer with organization;
+- do not present a document-side technical field as a business truth unless that mapping is proven.
+
+## Business usefulness rules
+
+An answer is not accepted as business-useful when any of these are true:
+- the direct answer is not placed first;
+- the answer opens with technical hedging instead of the user-facing result;
+- a weaker question is answered than the one the user asked;
+- the answer requires the user to reconstruct the conclusion from low-level evidence;
+- the answer uses ambiguous field labels for business-critical entities.
+
+## State continuity rules
+
+Follow-up continuity is a first-class acceptance object.
+
+The analyst must verify:
+- selected object continuity;
+- date/period continuity;
+- reusable evidence continuity;
+- pronoun resolution continuity.
+
+Important pronoun examples:
+- `эту позицию`
+- `этот товар`
+- `его`
+- `по нему`
+- `по этой позиции`
+
+If the previous turn already resolved a concrete object, the next turn must reuse it instead of asking for the anchor again.
+
+## Reusable answer-object cache
+
+For follow-up-heavy domains, the analyst should explicitly look for evidence that the product behaves as if it had a reusable resolved object bundle.
+
+Examples:
+- `current_item`
+- `current_as_of_date`
+- `current_provenance_trace`
+- `current_sale_trace`
+- `first_purchase_date`
+- `supplier_if_known`
+- `source_document_if_known`
+
+If the runtime recomputes everything from scratch and loses the already resolved object, call that out as a state-layer defect.
+
+## Root-cause layers
+
+Use one or more of these root-cause layers explicitly:
+- `semantic_understanding_gap`
+- `runtime_capability_gap`
+- `edge_carryover_gap`
+- `object_memory_gap`
+- `field_mapping_gap`
+- `answer_shape_mismatch`
+- `ordering_semantics_mismatch`
+- `business_utility_gap`
+- `loop_coverage_gap`
+- `domain_anchor_gap`
+
+## Minimum machine-readable verdict fields
+
+The analyst verdict should expose at least:
+- `user_intent_summary`
+- `expected_direct_answer`
+- `actual_direct_answer`
+- `direct_answer_ok`
+- `business_usefulness_ok`
+- `business_utility_score`
+- `direct_answer_priority_score`
+- `state_continuity_score`
+- `answer_shape_score`
+- `evidence_clarity_score`
+- `root_cause_layers`
+- `broken_edge_ids`
+- `violated_invariants`
+
+## Inventory-specific reminders
+
+For inventory follow-up chains, verify all of these:
+- the selected item remains the current focus object after the user clicks a result;
+- provenance questions answer supplier/date/document first, not only raw movement rows;
+- `когда купили` can reuse the already resolved provenance bundle;
+- supplier and organization are not mixed up in the surfaced answer;
+- `на эту дату` keeps the original stock date unless the user explicitly changed it.

.codex/skills/domain-case-loop/references/case_brief_template.md

@@ -9,6 +9,10 @@
 ## Expected business meaning
 - ...
 
+## Expected direct answer
+- first line should say:
+- minimum acceptable business answer:
+
 ## Expected capability
 - ...
 
@@ -31,6 +35,13 @@
 - warehouse if relevant
 - organization if relevant
 - expected answer shape
+- direct-answer-first when the user asked a direct lookup question
+- reusable resolved-object continuity when the user asks a follow-up about the same selected object
+
+## Field truth constraints
+- do not confuse supplier with organization
+- do not confuse buyer with organization
+- do not surface technical document-side fields as business truth without proof
 
 ## Contour status
 - in_contour / outside_current_contour / unknown
@@ -53,3 +64,5 @@
 - root node works
 - critical edges on the primary user path work
 - colloquial and UI-generated follow-up variants work
+- direct answer is placed first where expected
+- output is business-useful, not only technically grounded

.codex/skills/domain-case-loop/references/scenario_tree_acceptance_canon.md

@@ -12,6 +12,16 @@ The unit of acceptance is a **scenario tree**:
 
 If the root works but a critical child transition breaks, the domain is **not** hardened.
 
+## Business-first framing
+
+Every accepted node or edge must be both technically grounded and business-useful.
+
+This means:
+- the direct answer is surfaced first when the user asked a direct lookup question;
+- the answer stays on the requested business object;
+- evidence and caveats support the answer instead of replacing it;
+- field labels are truthful for business entities such as supplier, buyer, organization, warehouse, and document.
+
 ## Model the domain as a tree
 
 For each scenario, define:
@@ -36,7 +46,8 @@ A node is considered covered only if all of these are true:
 - the expected intent / capability is selected;
 - the answer shape matches the requested business object;
 - the answer begins with a direct user-facing answer when such an answer is expected;
-- the answer is evidence-backed rather than heuristic-masked.
+- the answer is evidence-backed rather than heuristic-masked;
+- the surfaced business fields are truthful and not mislabeled.
 
 Examples:
 - asking for supplier provenance must answer with the supplier first, not only with raw documents;
@@ -53,9 +64,23 @@ Typical invariants:
 - warehouse survives if the follow-up still targets the same stock slice
 - organization survives if the previous slice was organization-bound
 - route family remains in the same business contour unless the user clearly changed intent
+- reusable resolved-object state survives when the previous turn already answered a closely related lookup
+- pronoun references can reuse the active focus object when the wording supports it
 
 If an edge loses a required invariant, that is a real regression even if the target node works in isolation.
 
+## Resolved answer-object continuity
+
+For follow-up-heavy domains, the analyst should treat resolved business objects as reusable state, not as disposable one-turn artifacts.
+
+Examples:
+- selected inventory item
+- resolved supplier provenance bundle
+- resolved buyer bundle
+- resolved purchase document bundle
+
+If turn N already resolved such an object and turn N+1 asks a natural follow-up about the same object, the system should reuse that state instead of demanding the same anchor again.
+
 ## Mandatory paraphrase families
 
 Every critical node or edge must be validated in a small paraphrase family instead of one curated wording only.
@@ -65,11 +90,6 @@ Minimum family:
 - `colloquial`
 - `ui_selected_object`
 
-Examples:
-- canonical: `От какого поставщика куплен товар X`
-- colloquial: `Кто поставил этот товар`
-- ui_selected_object: `По выбранному объекту "X": кто это поставил нам`
-
 If canonical works but colloquial or UI-generated follow-up fails, the node/edge is not accepted.
 
 ## Acceptance matrix
@@ -86,6 +106,8 @@ Minimum matrix columns:
 - expected capability / recipe
 - required carryover invariants
 - expected answer shape
+- expected direct answer
+- business usefulness expectation
 - actual outcome
 - status (`pass`, `partial`, `fail`)
 - defect class
@@ -95,17 +117,25 @@ Minimum matrix columns:
 Use these classes explicitly:
 - `semantic_understanding_gap`
 - `edge_carryover_gap`
+- `object_memory_gap`
+- `field_mapping_gap`
 - `answer_shape_mismatch`
 - `ordering_semantics_mismatch`
 - `runtime_capability_gap`
+- `business_utility_gap`
+- `domain_anchor_gap`
 - `loop_coverage_gap`
 
 Definitions:
 - `semantic_understanding_gap`: the system did not understand the real user meaning
 - `edge_carryover_gap`: the follow-up lost date / object / scope across steps
+- `object_memory_gap`: the system resolved the object once but failed to retain it for the next follow-up
+- `field_mapping_gap`: the answer surfaced the wrong business field or mislabeled a field
 - `answer_shape_mismatch`: the business object in the answer does not match the requested object
 - `ordering_semantics_mismatch`: ranking / chronology semantics are wrong
 - `runtime_capability_gap`: the product contour truly lacks the route / intent / capability / extractor / recipe
+- `business_utility_gap`: the answer may be grounded but is still not useful as a user-facing result
+- `domain_anchor_gap`: the scenario uses a weak or wrong observed anchor, so the tree is semantically mis-specified
 - `loop_coverage_gap`: the runtime could support the path or nearly support it, but the analyst/orchestrator never treated that path as mandatory acceptance coverage
 
 ## Analyst responsibilities
@@ -116,6 +146,9 @@ The analyst must:
 - call out broken edges explicitly;
 - verify colloquial and UI-generated variants as first-class coverage;
 - verify direct-answer-first behavior where the user asked a direct lookup question;
+- verify business usefulness explicitly, not only technical validity;
+- verify field truthfulness for surfaced supplier / buyer / organization labels;
+- verify selected-object continuity and reusable object memory;
 - verify answer granularity and ordering semantics;
 - lower the score when any critical edge or paraphrase family is broken.
 
@@ -136,7 +169,9 @@ Do not accept a domain when:
 - selected-object follow-up is broken;
 - `на эту дату` / `на ту дату` loses the originating date;
 - the answer shape is wrong for the business question;
-- chronology / ranking semantics are inverted.
+- chronology / ranking semantics are inverted;
+- the direct answer is not surfaced first on direct lookup questions;
+- the answer is technically grounded but still business-useless.
 
 Accepted requires:
 - score >= 80
@@ -144,3 +179,5 @@ Accepted requires:
 - critical path edges pass
 - canonical + colloquial + UI-selected-object variants pass for critical branches
 - no silent heuristic masking
+- `direct_answer_ok = true`
+- `business_usefulness_ok = true`

.codex/skills/domain-case-loop/references/verdict_template.md

@@ -1,55 +1,74 @@
 # Verdict
 
-## 1. Смысл вопроса
+## 1. Question meaning
 ...
 
-## 2. Главный пользовательский путь и дерево сценария
+## 2. Primary user path and scenario tree
 - root:
 - critical child nodes:
 - critical edges:
 - primary user path:
 
-## 3. Что реально посчитано
+## 3. Expected direct answer
+- what the first line should say:
+- minimum acceptable business answer:
+
+## 4. What the system actually computed
 ...
 
-## 4. Где расхождение по бизнес-смыслу
+## 5. Business mismatch
+- did the answer solve the user's real question:
+- did the direct answer appear first:
+- is the answer usable for an operator/accountant/manager:
+
+## 6. Route / capability mismatch
 ...
 
-## 5. Где route / capability mismatch
+## 7. State continuity and selected-object memory
-...
+- selected object continuity:
+- date/period continuity:
+- reusable answer-object continuity:
+- pronoun resolution continuity:
 
-## 6. Evidence quality
+## 8. Field truth and evidence quality
-- exact / partial / heuristic / technical insufficiency
+- supplier vs organization:
-- why
+- buyer vs organization:
+- exact / partial / heuristic / technical insufficiency:
+- why:
 
-## 7. P0 defects
+## 9. P0 defects
 - ...
 
-## 8. P1 defects
+## 10. P1 defects
 - ...
 
-## 9. P2 defects
+## 11. P2 defects
 - ...
 
-## 10. Minimal patch directions
+## 12. Minimal patch directions
 - ...
 
-## 11. Acceptance matrix for rerun
+## 13. Acceptance matrix for rerun
 - Node / edge coverage:
 - Canonical wording:
 - Colloquial wording:
 - UI-generated selected-object wording:
 - Carryover invariants:
 - Expected answer shape:
+- Expected direct answer:
+- Business usefulness:
 - Defect class:
 
-## 12. Acceptance criteria for rerun
+## 14. Acceptance criteria for rerun
 - ...
 - Include colloquial/slang variants and UI-generated selected-object follow-up variants when they are part of the business flow.
 - Require the primary user path to pass end-to-end, not only the root node.
+- Require direct-answer-first behavior on direct lookup questions.
+- Require business-useful output rather than technically-grounded-but-noisy output.
+- Require selected-object continuity and reusable answer-object continuity on follow-up chains.
 
-## 13. Quality score
+## 15. Quality score
 - integer from 0 to 100
 
-## 14. Loop decision
+## 16. Loop decision
 - accepted / continue / partial / blocked / needs_exact_capability

AGENTS.md

@@ -26,6 +26,7 @@ Rules:
 - Do not accept a domain when only the root snapshot works but selected-object or drilldown follow-up edges still fail.
 - For critical branches, validate at least canonical wording, colloquial wording, and UI-generated selected-object wording when that UX exists.
 - Treat temporal carryover, selected-object carryover, answer-shape match, and ordering semantics as first-class acceptance invariants rather than optional polish.
+- Treat direct-answer-first behavior, business usefulness, selected-object memory, and field truthfulness as first-class analyst criteria rather than optional presentation polish.
 - If a case falls outside the current routed contour because the route/intent/capability is not wired yet, treat it as domain enablement work for this project, not as automatic out-of-scope rejection.
 - For new unmarked domains, `needs_exact_capability` means "bootstrap or extend the contour" rather than "close the case as unsupported".
 - A case can be marked `accepted` only when analyst verdict is at least `80/100`, no unresolved `P0` remains, and the rerun does not mask heuristic output as confirmed.

docs/orchestration/active_domain_contract.json

@@ -780,6 +780,12 @@
           "required_paraphrase_families": ["canonical", "ui_selected_object"],
           "required_carryover_invariants": ["selected_object", "date_scope", "answer_shape"]
         },
+        "bindings": {
+          "target_date_historical": "2020-03-31",
+          "focus_item_historical": "Шкаф картотечный 1000*400*2100",
+          "observed_supplier_candidate": "Гамма-мебель, ООО",
+          "observed_customer_candidate": "Департамент капитального ремонта города Москвы"
+        },
         "steps": [
           {
             "step_id": "step_01_account_41_historical",
@@ -790,7 +796,7 @@
             "title": "Historical account 41 anchor",
             "question": "Какие товары числятся на 41 счете на дату {{bindings.target_date_historical}}",
             "analysis_context": {
-              "as_of_date": "2019-03-31",
+              "as_of_date": "2020-03-31",
               "source": "binding_target_date_historical"
             },
             "expected_capability": "confirmed_inventory_on_hand_as_of_date",
@@ -823,13 +829,29 @@
             "node_role": "supporting_child",
             "paraphrase_family": "canonical",
             "title": "Supplier to buyer overlap",
-            "question": "Какие товары были куплены у поставщика {{bindings.observed_supplier_candidate}} и позже проданы покупателю {{bindings.observed_customer_candidate}}",
+            "question": "Есть ли документально подтвержденная цепочка: поставщик {{bindings.observed_supplier_candidate}} -> товар {{bindings.focus_item_historical}} -> покупатель {{bindings.observed_customer_candidate}}",
             "depends_on": ["step_01_account_41_historical", "step_02_selected_item_buyer"]
           }
         ]
       }
     ]
   },
+  "agent_audit_expectations": {
+    "direct_answer_first": true,
+    "business_utility_required": true,
+    "state_continuity_required": true,
+    "selected_object_memory_required": true,
+    "field_truth_checks": [
+      "supplier_vs_organization",
+      "buyer_vs_organization"
+    ],
+    "reusable_answer_object_expectations": [
+      "current_item",
+      "current_as_of_date",
+      "current_provenance_trace",
+      "current_sale_trace"
+    ]
+  },
   "acceptance_contract": {
     "acceptance_unit": "scenario_tree",
     "do_not_accept_if": [

docs/orchestration/schemas/domain_loop_analyst_verdict.schema.json

@@ -5,13 +5,26 @@
   "additionalProperties": false,
   "required": [
     "summary",
+    "user_intent_summary",
+    "expected_direct_answer",
+    "actual_direct_answer",
     "quality_score",
+    "direct_answer_ok",
+    "business_usefulness_ok",
+    "business_utility_score",
+    "direct_answer_priority_score",
+    "state_continuity_score",
+    "answer_shape_score",
+    "evidence_clarity_score",
     "loop_decision",
     "requires_user_decision",
     "user_decision_type",
     "user_decision_prompt",
     "unresolved_p0_count",
     "regression_detected",
+    "root_cause_layers",
+    "broken_edge_ids",
+    "violated_invariants",
     "priority_targets",
     "acceptance_criteria",
     "notes"
@@ -20,11 +33,51 @@
     "summary": {
       "type": "string"
     },
+    "user_intent_summary": {
+      "type": "string"
+    },
+    "expected_direct_answer": {
+      "type": "string"
+    },
+    "actual_direct_answer": {
+      "type": ["string", "null"]
+    },
     "quality_score": {
       "type": "integer",
       "minimum": 0,
       "maximum": 100
     },
+    "direct_answer_ok": {
+      "type": "boolean"
+    },
+    "business_usefulness_ok": {
+      "type": "boolean"
+    },
+    "business_utility_score": {
+      "type": "integer",
+      "minimum": 0,
+      "maximum": 100
+    },
+    "direct_answer_priority_score": {
+      "type": "integer",
+      "minimum": 0,
+      "maximum": 100
+    },
+    "state_continuity_score": {
+      "type": "integer",
+      "minimum": 0,
+      "maximum": 100
+    },
+    "answer_shape_score": {
+      "type": "integer",
+      "minimum": 0,
+      "maximum": 100
+    },
+    "evidence_clarity_score": {
+      "type": "integer",
+      "minimum": 0,
+      "maximum": 100
+    },
     "loop_decision": {
       "type": "string",
       "enum": ["accepted", "continue", "partial", "blocked", "needs_exact_capability"]
@@ -35,7 +88,17 @@
     },
     "user_decision_type": {
       "type": "string",
-      "enum": ["none", "architecture_fork", "important_business_question", "scope_tradeoff", "data_truth_gap", "missing_required_observation", "risky_workaround", "risky_complexity", "other"],
+      "enum": [
+        "none",
+        "architecture_fork",
+        "important_business_question",
+        "scope_tradeoff",
+        "data_truth_gap",
+        "missing_required_observation",
+        "risky_workaround",
+        "risky_complexity",
+        "other"
+      ],
       "description": "Explain why the loop needs user input. Use none when requires_user_decision is false."
     },
     "user_decision_prompt": {
@@ -49,6 +112,37 @@
     "regression_detected": {
       "type": "boolean"
     },
+    "root_cause_layers": {
+      "type": "array",
+      "items": {
+        "type": "string",
+        "enum": [
+          "semantic_understanding_gap",
+          "runtime_capability_gap",
+          "edge_carryover_gap",
+          "object_memory_gap",
+          "field_mapping_gap",
+          "answer_shape_mismatch",
+          "ordering_semantics_mismatch",
+          "business_utility_gap",
+          "loop_coverage_gap",
+          "domain_anchor_gap",
+          "other"
+        ]
+      }
+    },
+    "broken_edge_ids": {
+      "type": "array",
+      "items": {
+        "type": "string"
+      }
+    },
+    "violated_invariants": {
+      "type": "array",
+      "items": {
+        "type": "string"
+      }
+    },
     "priority_targets": {
       "type": "array",
       "items": {
@@ -68,7 +162,23 @@
           },
           "problem_type": {
             "type": "string",
-            "enum": ["route_gap", "capability_gap", "evidence_gap", "presentation_gap", "regression", "other"]
+            "enum": [
+              "route_gap",
+              "capability_gap",
+              "evidence_gap",
+              "presentation_gap",
+              "semantic_understanding_gap",
+              "edge_carryover_gap",
+              "object_memory_gap",
+              "field_mapping_gap",
+              "answer_shape_mismatch",
+              "ordering_semantics_mismatch",
+              "business_utility_gap",
+              "loop_coverage_gap",
+              "domain_anchor_gap",
+              "regression",
+              "other"
+            ]
           },
           "fix_goal": {
             "type": "string"

llm_normalizer/backend/dist/services/addressIntentResolver.js

@@ -1340,6 +1340,17 @@ function hasInventoryPurchaseDocumentsSignal(text) {
 function hasInventorySaleTraceSignal(text) {
     return /(?:продаж|покупател|buyer|sale trace|purchase[\s-]?to[\s-]?sale|purchase -> warehouse -> sale|закупка.*продаж)/iu.test(text);
 }
+function hasSelectedObjectInventoryCue(text) {
+    return /(?:по\s+выбранному\s+объекту|selected\s+object)/iu.test(text);
+}
+function hasSelectedObjectInventoryProvenanceSignal(text) {
+    return (hasSelectedObjectInventoryCue(text) &&
+        /(?:кто\s+(?:(?:это|этот\s+товар|эту\s+позицию)\s+)?(?:нам\s+)?поставил|кто\s+(?:нам\s+)?поставил\s+(?:это|этот\s+товар|эту\s+позицию)|от\s+какого\s+поставщика|у\s+какого\s+поставщика|от\s+кого\s+куплен|supplier|vendor|поставщик)/iu.test(text));
+}
+function hasSelectedObjectInventoryPurchaseDocumentsSignal(text) {
+    return (hasSelectedObjectInventoryCue(text) &&
+        /(?:по\s+каким\s+документам\s+(?:это|его|этот\s+товар|эту\s+позицию)\s+купили|по\s+каким\s+документам\s+(?:был\s+)?куплен|какими\s+документами\s+(?:это|его|этот\s+товар|эту\s+позицию)\s+купили|какими\s+документами\s+(?:был\s+)?куплен|purchase\s+documents|documents\s+of\s+purchase|through\s+which\s+documents)/iu.test(text));
+}
 function hasInventoryProvenanceSignalV2(text) {
     const hasItemCue = /(?:товар|номенклатур|sku|item|product|остат(?:ок|ки)|склад)/iu.test(text);
     const hasSupplierCue = /(?:от\s+какого\s+поставщика|у\s+какого\s+поставщика|от\s+кого\s+куплен|кто\s+(?:нам\s+)?поставил|кем\s+поставлен|поставщик|supplier|vendor)/iu.test(text);
@@ -1541,6 +1552,13 @@ function resolveAddressIntent(userMessage) {
             reasons: ["inventory_aging_signal_detected"]
         };
     }
+    if (hasSelectedObjectInventoryProvenanceSignal(text)) {
+        return {
+            intent: "inventory_purchase_provenance_for_item",
+            confidence: "medium",
+            reasons: ["inventory_selected_object_provenance_signal_detected"]
+        };
+    }
     if (hasInventoryProvenanceSignalV2(text)) {
         return {
             intent: "inventory_purchase_provenance_for_item",
@@ -1555,6 +1573,13 @@ function resolveAddressIntent(userMessage) {
             reasons: ["inventory_purchase_date_signal_detected"]
         };
     }
+    if (hasSelectedObjectInventoryPurchaseDocumentsSignal(text)) {
+        return {
+            intent: "inventory_purchase_documents_for_item",
+            confidence: "medium",
+            reasons: ["inventory_selected_object_purchase_documents_signal_detected"]
+        };
+    }
     if (hasInventoryPurchaseDocumentsSignalV2(text)) {
         return {
             intent: "inventory_purchase_documents_for_item",

llm_normalizer/backend/dist/services/addressQueryService.js

@@ -2879,6 +2879,19 @@ class AddressQueryService {
                         const broadenedFactual = (0, composeStage_1.composeFactualReply)(intent.intent, broadenedFilteredRows, composeOptionsFromFilters(autoBroadenedFilters));
                         const broadenedLimitations = [...filters.warnings, "period_window_auto_broadened_to_available_data"];
                         const broadenedReasons = [...baseReasons, "period_window_auto_broadened_to_available_data"];
+                        const broadenedResultSemantics = mergeAddressResultSemantics(deriveAddressResultSemantics({
+                            intent: intent.intent,
+                            selectedRecipe: broadenedSelection.selected_recipe.recipe_id,
+                            filters: filters.extracted_filters,
+                            responseType: broadenedFactual.responseType,
+                            rowsMatched: broadenedFilteredRows.length
+                        }), broadenedFactual.semantics);
+                        const broadenedRouteExpectationAudit = buildRouteExpectationAudit({
+                            intent: routeExpectationIntent,
+                            selectedRecipe: broadenedSelection.selected_recipe.recipe_id,
+                            requestedResultMode,
+                            resultMode: broadenedResultSemantics.result_mode
+                        });
                         return {
                             handled: true,
                             reply_text: injectNoticeAfterLeadLine(broadenedFactual.text, broadenedPrefix),
@@ -2921,13 +2934,20 @@ class AddressQueryService {
                                 runtime_readiness: "LIVE_QUERYABLE_WITH_LIMITS",
                                 limited_reason_category: null,
                                 response_type: broadenedFactual.responseType,
-                                ...mergeAddressResultSemantics(deriveAddressResultSemantics({
+                                capability_id: capabilityAudit.capabilityId,
-                                    intent: intent.intent,
+                                capability_layer: capabilityAudit.layer,
-                                    selectedRecipe: broadenedSelection.selected_recipe.recipe_id,
+                                capability_route_mode: capabilityAudit.routeMode,
-                                    filters: filters.extracted_filters,
+                                capability_route_enabled: capabilityAudit.enabled,
-                                    responseType: broadenedFactual.responseType,
+                                capability_route_reason: capabilityAudit.reason,
-                                    rowsMatched: broadenedFilteredRows.length
+                                shadow_route_intent: shadowRouteAudit.intent,
-                                }), broadenedFactual.semantics),
+                                shadow_route_selected_recipe: shadowRouteAudit.selectedRecipe,
+                                shadow_route_status: shadowRouteAudit.status,
+                                route_expectation_status: broadenedRouteExpectationAudit.status,
+                                route_expectation_reason: broadenedRouteExpectationAudit.reason,
+                                route_expectation_expected_selected_recipes: broadenedRouteExpectationAudit.expectedSelectedRecipes,
+                                route_expectation_expected_requested_result_modes: broadenedRouteExpectationAudit.expectedRequestedResultModes,
+                                route_expectation_expected_result_modes: broadenedRouteExpectationAudit.expectedResultModes,
+                                ...broadenedResultSemantics,
                                 limitations: broadenedLimitations,
                                 reasons: withConfirmedBalanceFallbackReason(broadenedReasons, requestedResultMode, broadenedFactual.semantics)
                             }

llm_normalizer/backend/dist/services/address_runtime/decomposeStage.js

@@ -244,6 +244,24 @@ function mapCounterpartyIntentToContractIntent(intent) {
     }
     return null;
 }
+function isInventoryIntent(intent) {
+    return (intent === "inventory_on_hand_as_of_date" ||
+        intent === "inventory_purchase_provenance_for_item" ||
+        intent === "inventory_purchase_documents_for_item" ||
+        intent === "inventory_supplier_stock_overlap_as_of_date" ||
+        intent === "inventory_sale_trace_for_item" ||
+        intent === "inventory_purchase_to_sale_chain" ||
+        intent === "inventory_aging_by_purchase_date");
+}
+function hasSelectedObjectInventorySignal(text) {
+    return /(?:по\s+выбранному\s+объекту|for\s+selected\s+object)/iu.test(String(text ?? ""));
+}
+function hasInventorySupplierFollowupCue(text) {
+    return /(?:кто\s+(?:(?:это|этот\s+товар|эту\s+позицию)\s+)?(?:нам\s+)?поставил|кто\s+(?:нам\s+)?поставил\s+(?:это|этот\s+товар|эту\s+позицию)|от\s+какого\s+поставщика|у\s+какого\s+поставщика|от\s+кого\s+куплен|supplier|vendor|поставщик)/iu.test(String(text ?? ""));
+}
+function hasInventoryPurchaseDocumentsFollowupCue(text) {
+    return /(?:по\s+каким\s+документам\s+(?:это|его|этот\s+товар|эту\s+позицию)\s+купили|по\s+каким\s+документам\s+(?:был\s+)?куплен|какими\s+документами\s+(?:это|его|этот\s+товар|эту\s+позицию)\s+купили|какими\s+документами\s+(?:был\s+)?куплен|purchase\s+documents|documents\s+of\s+purchase|through\s+which\s+documents)/iu.test(String(text ?? ""));
+}
 function hasAddressFollowupContextSignal(text) {
     const normalized = String(text ?? "").trim();
     if (!normalized) {
@@ -612,6 +630,32 @@ function deriveIntentWithFollowupContext(detectedIntent, userMessage, followupCo
             reasons: [...detectedIntent.reasons, "intent_adjusted_to_balance_followup_context"]
         };
     }
+    const previousIsInventoryFamily = isInventoryIntent(previousIntent);
+    const inventorySelectedObjectFollowup = hasSelectedObjectInventorySignal(normalizedMessage) || (previousIsInventoryFamily && hasFollowupSignal);
+    if (inventorySelectedObjectFollowup && hasInventorySupplierFollowupCue(normalizedMessage)) {
+        if (detectedIntent.intent === "unknown" ||
+            detectedIntent.intent === "inventory_on_hand_as_of_date" ||
+            detectedIntent.intent === previousIntent) {
+            return {
+                intent: "inventory_purchase_provenance_for_item",
+                confidence: "low",
+                reasons: [...detectedIntent.reasons, "intent_adjusted_to_inventory_followup_context"]
+            };
+        }
+    }
+    if (inventorySelectedObjectFollowup && hasInventoryPurchaseDocumentsFollowupCue(normalizedMessage)) {
+        if (detectedIntent.intent === "unknown" ||
+            detectedIntent.intent === "list_documents_by_counterparty" ||
+            detectedIntent.intent === "list_documents_by_contract" ||
+            detectedIntent.intent === "inventory_on_hand_as_of_date" ||
+            detectedIntent.intent === previousIntent) {
+            return {
+                intent: "inventory_purchase_documents_for_item",
+                confidence: "low",
+                reasons: [...detectedIntent.reasons, "intent_adjusted_to_inventory_followup_context"]
+            };
+        }
+    }
     if (hasPreviousContract) {
         if (detectedIntent.intent === "list_contracts_by_counterparty") {
             if (hasBankSignal(normalizedMessage)) {

llm_normalizer/backend/src/services/addressIntentResolver.ts

@@ -1603,6 +1603,28 @@ function hasInventorySaleTraceSignal(text: string): boolean {
   );
 }
 
+function hasSelectedObjectInventoryCue(text: string): boolean {
+  return /(?:по\s+выбранному\s+объекту|selected\s+object)/iu.test(text);
+}
+
+function hasSelectedObjectInventoryProvenanceSignal(text: string): boolean {
+  return (
+    hasSelectedObjectInventoryCue(text) &&
+    /(?:кто\s+(?:(?:это|этот\s+товар|эту\s+позицию)\s+)?(?:нам\s+)?поставил|кто\s+(?:нам\s+)?поставил\s+(?:это|этот\s+товар|эту\s+позицию)|от\s+какого\s+поставщика|у\s+какого\s+поставщика|от\s+кого\s+куплен|supplier|vendor|поставщик)/iu.test(
+      text
+    )
+  );
+}
+
+function hasSelectedObjectInventoryPurchaseDocumentsSignal(text: string): boolean {
+  return (
+    hasSelectedObjectInventoryCue(text) &&
+    /(?:по\s+каким\s+документам\s+(?:это|его|этот\s+товар|эту\s+позицию)\s+купили|по\s+каким\s+документам\s+(?:был\s+)?куплен|какими\s+документами\s+(?:это|его|этот\s+товар|эту\s+позицию)\s+купили|какими\s+документами\s+(?:был\s+)?куплен|purchase\s+documents|documents\s+of\s+purchase|through\s+which\s+documents)/iu.test(
+      text
+    )
+  );
+}
+
 function hasInventoryProvenanceSignalV2(text: string): boolean {
   const hasItemCue = /(?:товар|номенклатур|sku|item|product|остат(?:ок|ки)|склад)/iu.test(text);
   const hasSupplierCue =
@@ -1871,6 +1893,14 @@ export function resolveAddressIntent(userMessage: string): AddressIntentResoluti
     };
   }
 
+  if (hasSelectedObjectInventoryProvenanceSignal(text)) {
+    return {
+      intent: "inventory_purchase_provenance_for_item",
+      confidence: "medium",
+      reasons: ["inventory_selected_object_provenance_signal_detected"]
+    };
+  }
+
   if (hasInventoryProvenanceSignalV2(text)) {
     return {
       intent: "inventory_purchase_provenance_for_item",
@@ -1887,6 +1917,14 @@ export function resolveAddressIntent(userMessage: string): AddressIntentResoluti
     };
   }
 
+  if (hasSelectedObjectInventoryPurchaseDocumentsSignal(text)) {
+    return {
+      intent: "inventory_purchase_documents_for_item",
+      confidence: "medium",
+      reasons: ["inventory_selected_object_purchase_documents_signal_detected"]
+    };
+  }
+
   if (hasInventoryPurchaseDocumentsSignalV2(text)) {
     return {
       intent: "inventory_purchase_documents_for_item",

llm_normalizer/backend/src/services/addressQueryService.ts

@@ -3498,6 +3498,22 @@ export class AddressQueryService {
             );
             const broadenedLimitations = [...filters.warnings, "period_window_auto_broadened_to_available_data"];
             const broadenedReasons = [...baseReasons, "period_window_auto_broadened_to_available_data"];
+            const broadenedResultSemantics = mergeAddressResultSemantics(
+              deriveAddressResultSemantics({
+                intent: intent.intent,
+                selectedRecipe: broadenedSelection.selected_recipe.recipe_id,
+                filters: filters.extracted_filters,
+                responseType: broadenedFactual.responseType,
+                rowsMatched: broadenedFilteredRows.length
+              }),
+              broadenedFactual.semantics
+            );
+            const broadenedRouteExpectationAudit = buildRouteExpectationAudit({
+              intent: routeExpectationIntent,
+              selectedRecipe: broadenedSelection.selected_recipe.recipe_id,
+              requestedResultMode,
+              resultMode: broadenedResultSemantics.result_mode
+            });
             return {
               handled: true,
               reply_text: injectNoticeAfterLeadLine(broadenedFactual.text, broadenedPrefix),
@@ -3540,16 +3556,21 @@ export class AddressQueryService {
                 runtime_readiness: "LIVE_QUERYABLE_WITH_LIMITS",
                 limited_reason_category: null,
                 response_type: broadenedFactual.responseType,
-                ...mergeAddressResultSemantics(
+                capability_id: capabilityAudit.capabilityId,
-                  deriveAddressResultSemantics({
+                capability_layer: capabilityAudit.layer,
-                    intent: intent.intent,
+                capability_route_mode: capabilityAudit.routeMode,
-                    selectedRecipe: broadenedSelection.selected_recipe.recipe_id,
+                capability_route_enabled: capabilityAudit.enabled,
-                    filters: filters.extracted_filters,
+                capability_route_reason: capabilityAudit.reason,
-                    responseType: broadenedFactual.responseType,
+                shadow_route_intent: shadowRouteAudit.intent,
-                    rowsMatched: broadenedFilteredRows.length
+                shadow_route_selected_recipe: shadowRouteAudit.selectedRecipe,
-                  }),
+                shadow_route_status: shadowRouteAudit.status,
-                  broadenedFactual.semantics
+                route_expectation_status: broadenedRouteExpectationAudit.status,
-                ),
+                route_expectation_reason: broadenedRouteExpectationAudit.reason,
+                route_expectation_expected_selected_recipes: broadenedRouteExpectationAudit.expectedSelectedRecipes,
+                route_expectation_expected_requested_result_modes:
+                  broadenedRouteExpectationAudit.expectedRequestedResultModes,
+                route_expectation_expected_result_modes: broadenedRouteExpectationAudit.expectedResultModes,
+                ...broadenedResultSemantics,
                 limitations: broadenedLimitations,
                 reasons: withConfirmedBalanceFallbackReason(
                   broadenedReasons,

llm_normalizer/backend/src/services/address_runtime/decomposeStage.ts

@@ -306,6 +306,34 @@ function mapCounterpartyIntentToContractIntent(intent: AddressIntent): AddressIn
   return null;
 }
 
+function isInventoryIntent(intent: AddressIntent | undefined): boolean {
+  return (
+    intent === "inventory_on_hand_as_of_date" ||
+    intent === "inventory_purchase_provenance_for_item" ||
+    intent === "inventory_purchase_documents_for_item" ||
+    intent === "inventory_supplier_stock_overlap_as_of_date" ||
+    intent === "inventory_sale_trace_for_item" ||
+    intent === "inventory_purchase_to_sale_chain" ||
+    intent === "inventory_aging_by_purchase_date"
+  );
+}
+
+function hasSelectedObjectInventorySignal(text: string): boolean {
+  return /(?:по\s+выбранному\s+объекту|for\s+selected\s+object)/iu.test(String(text ?? ""));
+}
+
+function hasInventorySupplierFollowupCue(text: string): boolean {
+  return /(?:кто\s+(?:(?:это|этот\s+товар|эту\s+позицию)\s+)?(?:нам\s+)?поставил|кто\s+(?:нам\s+)?поставил\s+(?:это|этот\s+товар|эту\s+позицию)|от\s+какого\s+поставщика|у\s+какого\s+поставщика|от\s+кого\s+куплен|supplier|vendor|поставщик)/iu.test(
+    String(text ?? "")
+  );
+}
+
+function hasInventoryPurchaseDocumentsFollowupCue(text: string): boolean {
+  return /(?:по\s+каким\s+документам\s+(?:это|его|этот\s+товар|эту\s+позицию)\s+купили|по\s+каким\s+документам\s+(?:был\s+)?куплен|какими\s+документами\s+(?:это|его|этот\s+товар|эту\s+позицию)\s+купили|какими\s+документами\s+(?:был\s+)?куплен|purchase\s+documents|documents\s+of\s+purchase|through\s+which\s+documents)/iu.test(
+    String(text ?? "")
+  );
+}
+
 export function hasAddressFollowupContextSignal(text: string): boolean {
   const normalized = String(text ?? "").trim();
   if (!normalized) {
@@ -752,6 +780,39 @@ function deriveIntentWithFollowupContext(
     };
   }
 
+  const previousIsInventoryFamily = isInventoryIntent(previousIntent);
+  const inventorySelectedObjectFollowup =
+    hasSelectedObjectInventorySignal(normalizedMessage) || (previousIsInventoryFamily && hasFollowupSignal);
+  if (inventorySelectedObjectFollowup && hasInventorySupplierFollowupCue(normalizedMessage)) {
+    if (
+      detectedIntent.intent === "unknown" ||
+      detectedIntent.intent === "inventory_on_hand_as_of_date" ||
+      detectedIntent.intent === previousIntent
+    ) {
+      return {
+        intent: "inventory_purchase_provenance_for_item",
+        confidence: "low",
+        reasons: [...detectedIntent.reasons, "intent_adjusted_to_inventory_followup_context"]
+      };
+    }
+  }
+
+  if (inventorySelectedObjectFollowup && hasInventoryPurchaseDocumentsFollowupCue(normalizedMessage)) {
+    if (
+      detectedIntent.intent === "unknown" ||
+      detectedIntent.intent === "list_documents_by_counterparty" ||
+      detectedIntent.intent === "list_documents_by_contract" ||
+      detectedIntent.intent === "inventory_on_hand_as_of_date" ||
+      detectedIntent.intent === previousIntent
+    ) {
+      return {
+        intent: "inventory_purchase_documents_for_item",
+        confidence: "low",
+        reasons: [...detectedIntent.reasons, "intent_adjusted_to_inventory_followup_context"]
+      };
+    }
+  }
+
   if (hasPreviousContract) {
     if (detectedIntent.intent === "list_contracts_by_counterparty") {
       if (hasBankSignal(normalizedMessage)) {

llm_normalizer/backend/tests/addressInventorySelectedObjectFollowup.test.ts

@@ -103,6 +103,8 @@ describe("inventory selected-object follow-up", () => {
     expect(result?.debug.extracted_filters?.as_of_date).toBe("2021-03-31");
     expect(result?.debug.extracted_filters?.period_from).toBe("2021-03-01");
     expect(result?.debug.extracted_filters?.period_to).toBe("2021-03-31");
+    expect(result?.debug.capability_id).toBe("inventory_inventory_purchase_provenance_for_item");
+    expect(result?.debug.capability_route_mode).toBe("exact");
     expect(result?.debug.reasons).toContain("period_window_auto_broadened_to_available_data");
     expect(result?.debug.limitations).toContain("period_window_auto_broadened_to_available_data");
     const replyLines = String(result?.reply_text ?? "").split("\n");
@@ -111,4 +113,97 @@ describe("inventory selected-object follow-up", () => {
     expect(replyLines[1]).toContain("По окну 2021-03-01..2021-03-31 строк не найдено");
     expect(executeAddressMcpQueryMock).toHaveBeenCalledTimes(2);
   });
+
+  it("handles selected-object supplier slang 'кто это поставил нам' as provenance follow-up", async () => {
+    executeAddressMcpQueryMock.mockResolvedValueOnce({
+      fetched_rows: 1,
+      matched_rows: 1,
+      raw_rows: [
+        {
+          Period: "2019-02-11T00:00:00Z",
+          Registrator: "Поступление товаров и услуг 00000000077 от 11.02.2019 0:00:00",
+          AccountDt: "41.01",
+          AccountKt: "60.01",
+          Amount: 3724.17,
+          SubcontoDt1: "Столешница 600*3050*26 дуб ниагара",
+          SubcontoDt3: "Основной склад",
+          SubcontoKt1: "Торговый дом \\Союз МСК\\",
+          SubcontoKt2: "Договор поставки № 12 от 01.02.2019",
+          Organization: "ООО \\Альтернатива Плюс\\"
+        }
+      ],
+      rows: [],
+      error: null
+    });
+
+    const service = new AddressQueryService();
+    const result = await service.tryHandle('По выбранному объекту "Столешница 600*3050*26 дуб ниагара": кто это поставил нам', {
+      followupContext: {
+        previous_intent: "inventory_on_hand_as_of_date",
+        previous_filters: {
+          as_of_date: "2019-03-31",
+          period_from: "2019-03-01",
+          period_to: "2019-03-31",
+          warehouse: "Основной склад",
+          organization: "ООО \\Альтернатива Плюс\\"
+        },
+        previous_anchor_type: "unknown",
+        previous_anchor_value: null
+      }
+    });
+
+    expect(result?.handled).toBe(true);
+    expect(result?.response_type).toBe("FACTUAL_SUMMARY");
+    expect(result?.debug.detected_intent).toBe("inventory_purchase_provenance_for_item");
+    expect(result?.debug.extracted_filters?.item).toBe("Столешница 600*3050*26 дуб ниагара");
+    expect(result?.debug.extracted_filters?.as_of_date).toBe("2019-03-31");
+    expect(String(result?.reply_text ?? "")).toContain("Торговый дом \\Союз МСК\\");
+  });
+
+  it("handles selected-object purchase-doc slang 'по каким документам это купили' as exact purchase-doc follow-up", async () => {
+    executeAddressMcpQueryMock.mockResolvedValueOnce({
+      fetched_rows: 1,
+      matched_rows: 1,
+      raw_rows: [
+        {
+          Period: "2019-02-11T00:00:00Z",
+          Registrator: "Поступление товаров и услуг 00000000077 от 11.02.2019 0:00:00",
+          AccountDt: "41.01",
+          AccountKt: "60.01",
+          Amount: 3724.17,
+          SubcontoDt1: "Столешница 600*3050*26 дуб ниагара",
+          SubcontoDt3: "Основной склад",
+          SubcontoKt1: "Торговый дом \\Союз МСК\\",
+          SubcontoKt2: "Договор поставки № 12 от 01.02.2019",
+          Organization: "ООО \\Альтернатива Плюс\\"
+        }
+      ],
+      rows: [],
+      error: null
+    });
+
+    const service = new AddressQueryService();
+    const result = await service.tryHandle('По выбранному объекту "Столешница 600*3050*26 дуб ниагара": по каким документам это купили', {
+      followupContext: {
+        previous_intent: "inventory_purchase_provenance_for_item",
+        previous_filters: {
+          as_of_date: "2019-03-31",
+          period_from: "2019-03-01",
+          period_to: "2019-03-31",
+          item: "Столешница 600*3050*26 дуб ниагара",
+          warehouse: "Основной склад"
+        },
+        previous_anchor_type: "unknown",
+        previous_anchor_value: null
+      }
+    });
+
+    expect(result?.handled).toBe(true);
+    expect(result?.response_type).toBe("FACTUAL_LIST");
+    expect(result?.debug.detected_intent).toBe("inventory_purchase_documents_for_item");
+    expect(result?.debug.selected_recipe).toBe("address_inventory_purchase_documents_for_item_v1");
+    expect(result?.debug.extracted_filters?.item).toBe("Столешница 600*3050*26 дуб ниагара");
+    expect(result?.debug.extracted_filters?.as_of_date).toBe("2019-03-31");
+    expect(String(result?.reply_text ?? "")).toContain("Поступление товаров и услуг 00000000077");
+  });
 });

llm_normalizer/backend/tests/addressQueryRuntimeM23.test.ts

@@ -173,6 +173,14 @@ describe("address query shape classifier", () => {
     expect(filters.item).toBe("Кромка с клеем 33 альмандин 137 м");
   });
 
+  it("extracts item anchor from selected-object purchase-doc follow-up without explicit word товар", () => {
+    const filters = extractAddressFilters(
+      'По выбранному объекту "Столешница 600*3050*26 дуб ниагара": по каким документам это купили',
+      "inventory_purchase_documents_for_item"
+    ).extracted_filters;
+    expect(filters.item).toBe("Столешница 600*3050*26 дуб ниагара");
+  });
+
   it("keeps colloquial selected-object supplier follow-up in inventory provenance intent", () => {
     const mode = detectAddressQuestionMode(
       'По выбранному объекту "Кромка с клеем 33 альмандин 137 м": кто поставил этот товар'
@@ -184,6 +192,28 @@ describe("address query shape classifier", () => {
     expect(result.intent).toBe("inventory_purchase_provenance_for_item");
   });
 
+  it("keeps selected-object supplier slang with 'кто это поставил нам' in inventory provenance intent", () => {
+    const mode = detectAddressQuestionMode(
+      'По выбранному объекту "Столешница 600*3050*26 дуб ниагара": кто это поставил нам'
+    );
+    const result = resolveAddressIntent(
+      'По выбранному объекту "Столешница 600*3050*26 дуб ниагара": кто это поставил нам'
+    );
+    expect(mode.mode).toBe("address_query");
+    expect(result.intent).toBe("inventory_purchase_provenance_for_item");
+  });
+
+  it("keeps selected-object purchase-doc slang with 'по каким документам это купили' in purchase-doc intent", () => {
+    const mode = detectAddressQuestionMode(
+      'По выбранному объекту "Столешница 600*3050*26 дуб ниагара": по каким документам это купили'
+    );
+    const result = resolveAddressIntent(
+      'По выбранному объекту "Столешница 600*3050*26 дуб ниагара": по каким документам это купили'
+    );
+    expect(mode.mode).toBe("address_query");
+    expect(result.intent).toBe("inventory_purchase_documents_for_item");
+  });
+
   it("keeps full supplier anchor with comma suffix for stock-overlap questions", () => {
     const filters = extractAddressFilters(
       "Какие товары от поставщика Гамма-мебель, ООО сейчас еще лежат на складе Основной склад?",
@@ -3874,6 +3904,49 @@ describe("address query limited taxonomy and stage diagnostics", { timeout: 1500
 });
 
 describe("address decompose stage follow-up carryover", () => {
+  it("promotes selected-object supplier slang follow-up into inventory provenance with inherited date context", () => {
+    const result = runAddressDecomposeStage('По выбранному объекту "Столешница 600*3050*26 дуб ниагара": кто это поставил нам', {
+      previous_intent: "inventory_on_hand_as_of_date",
+      previous_filters: {
+        as_of_date: "2019-03-31",
+        period_from: "2019-03-01",
+        period_to: "2019-03-31",
+        warehouse: "Основной склад"
+      },
+      previous_anchor_type: "unknown",
+      previous_anchor_value: null
+    });
+    expect(result).not.toBeNull();
+    expect(result?.intent.intent).toBe("inventory_purchase_provenance_for_item");
+    expect(result?.filters.extracted_filters.as_of_date).toBe("2019-03-31");
+    expect(
+      result?.baseReasons?.includes("intent_adjusted_to_inventory_followup_context") ||
+        result?.intent.reasons.includes("inventory_selected_object_provenance_signal_detected")
+    ).toBe(true);
+  });
+
+  it("promotes selected-object purchase-doc slang follow-up into inventory purchase documents with inherited date context", () => {
+    const result = runAddressDecomposeStage('По выбранному объекту "Столешница 600*3050*26 дуб ниагара": по каким документам это купили', {
+      previous_intent: "inventory_purchase_provenance_for_item",
+      previous_filters: {
+        as_of_date: "2019-03-31",
+        period_from: "2019-03-01",
+        period_to: "2019-03-31",
+        item: "Столешница 600*3050*26 дуб ниагара"
+      },
+      previous_anchor_type: "unknown",
+      previous_anchor_value: null
+    });
+    expect(result).not.toBeNull();
+    expect(result?.intent.intent).toBe("inventory_purchase_documents_for_item");
+    expect(result?.filters.extracted_filters.item).toBe("Столешница 600*3050*26 дуб ниагара");
+    expect(result?.filters.extracted_filters.as_of_date).toBe("2019-03-31");
+    expect(
+      result?.baseReasons?.includes("intent_adjusted_to_inventory_followup_context") ||
+        result?.intent.reasons.includes("inventory_selected_object_purchase_documents_signal_detected")
+    ).toBe(true);
+  });
+
   it("keeps slang all-customers-all-time wording in address lane via resolved intent fallback", () => {
     const result = runAddressDecomposeStage("выведи всех заков за все время", null);
     expect(result).not.toBeNull();

scripts/domain_case_loop.py

@@ -2120,6 +2120,7 @@ def build_analyst_loop_prompt(
         - `.codex/agents/domain_analyst.toml`
         - `.codex/skills/domain-case-loop/SKILL.md`
         - `.codex/skills/domain-case-loop/references/verdict_template.md`
+        - `.codex/skills/domain-case-loop/references/business_first_analyst_rubric.md`
 
         Current loop context:
         - loop_dir: `{loop_dir}`
@@ -2135,11 +2136,13 @@ def build_analyst_loop_prompt(
 
         Goal:
         - evaluate current domain-pack correctness for business meaning, route/capability quality, evidence quality, and absence of silent heuristic masking;
+        - evaluate business usefulness, direct-answer-first behavior, state continuity, and field truthfulness, not only technical groundedness;
         - determine whether the gate `quality_score >= {target_score}` is reached;
         - if not, provide the smallest high-value fix targets for the coder.
 
         Rules:
         - `accepted` is allowed only if quality_score >= {target_score}, unresolved_p0_count = 0, and regression_detected = false;
+        - `accepted` also requires `direct_answer_ok = true` and `business_usefulness_ok = true`;
         - `partial` means the pack is usable but exactness, routing, or coverage is still insufficient;
         - `needs_exact_capability` means the primary blocker is a missing exact route or capability, but the loop should still continue autonomously unless a user decision is required;
         - `continue` means there is a clear next patch cycle;
@@ -2152,6 +2155,10 @@ def build_analyst_loop_prompt(
         - if `requires_user_decision = true`, fill `user_decision_type` and `user_decision_prompt`;
         - if the pack is below {target_score} but there is still safe autonomous implementation work, keep `requires_user_decision = false`;
         - do not request user input merely because the score is still below {target_score}; request it only when the loop would otherwise guess, overfit, or risk architecture drift.
+        - return machine-readable fields for: `user_intent_summary`, `expected_direct_answer`, `actual_direct_answer`, `direct_answer_ok`, `business_usefulness_ok`, `business_utility_score`, `direct_answer_priority_score`, `state_continuity_score`, `answer_shape_score`, `evidence_clarity_score`, `root_cause_layers`, `broken_edge_ids`, `violated_invariants`;
+        - if the product found the evidence but failed to retain the selected object, provenance bundle, or another reusable resolved object across turns, classify that as `object_memory_gap` or `edge_carryover_gap`, not as a generic route problem;
+        - if the surfaced business field looks mislabeled, for example supplier vs organization, classify that as `field_mapping_gap`;
+        - if the answer is technically grounded but still weak for a manager/accountant/operator, classify that as `business_utility_gap`.
 
         Use this UTF-8 evidence bundle as the source of truth for artifact contents. Do not treat shell rendering artifacts as file corruption if the embedded bundle is readable.
 
@@ -2196,6 +2203,9 @@ def build_coder_loop_prompt(
         - do not present heuristic answers as confirmed;
         - do not touch unrelated files;
         - preserve already successful baseline flows.
+        - use `root_cause_layers`, `broken_edge_ids`, `violated_invariants`, and business-utility scores from the analyst verdict to choose the smallest fix;
+        - prioritize state continuity, selected-object persistence, direct-answer-first behavior, and field-truth mapping when those are the blocking layers;
+        - do not broaden scope when the analyst says the defect is mainly `object_memory_gap`, `field_mapping_gap`, `answer_shape_mismatch`, or `business_utility_gap`.
 
         Required outputs:
         - create `{iteration_dir / 'coder_plan.md'}` with a short plan;
@@ -2217,12 +2227,21 @@ def evaluate_analyst_gate(
     quality_score = int(verdict.get("quality_score") or 0)
     unresolved_p0_count = int(verdict.get("unresolved_p0_count") or 0)
     regression_detected = bool(verdict.get("regression_detected"))
+    direct_answer_ok = bool(verdict.get("direct_answer_ok", True))
+    business_usefulness_ok = bool(verdict.get("business_usefulness_ok", True))
     loop_decision = str(verdict.get("loop_decision") or "").strip() or "continue"
     requires_user_decision = bool(verdict.get("requires_user_decision"))
     user_decision_type = str(verdict.get("user_decision_type") or "").strip() or "none"
     user_decision_prompt_raw = verdict.get("user_decision_prompt")
     user_decision_prompt = str(user_decision_prompt_raw).strip() if user_decision_prompt_raw else None
-    accepted = quality_score >= target_score and unresolved_p0_count == 0 and not regression_detected and loop_decision == "accepted"
+    accepted = (
+        quality_score >= target_score
+        and unresolved_p0_count == 0
+        and not regression_detected
+        and direct_answer_ok
+        and business_usefulness_ok
+        and loop_decision == "accepted"
+    )
     return accepted, loop_decision, requires_user_decision, user_decision_type, user_decision_prompt