Добавить dogfood-манифест stage-loop

docs/orchestration/agentic_semantic_development_loop_stage_pack.json

@@ -0,0 +1,100 @@
+{
+  "schema_version": "domain_scenario_pack_v1",
+  "pack_id": "agentic_semantic_development_loop_stage_pack",
+  "domain": "agentic_semantic_development_loop_control",
+  "title": "Agentic semantic development loop control pack",
+  "description": "Compact stage pack for dogfooding the agentic development loop against business-overview, VAT, stale-scope, and legacy-canary questions.",
+  "analysis_context": {
+    "as_of_date": "2026-05-09",
+    "source": "agentic_semantic_development_loop_stage_pack"
+  },
+  "bindings": {
+    "main_organization": "ООО Альтернатива Плюс",
+    "control_year": "2020",
+    "svk_counterparty": "Группа СВК"
+  },
+  "scenarios": [
+    {
+      "scenario_id": "agentic_loop_business_overview_control",
+      "title": "Business overview and stale-scope control",
+      "description": "Checks direct business-answer shape, period carryover, all-time reset, VAT boundary, and organization scope hygiene.",
+      "steps": [
+        {
+          "step_id": "step_01_business_overview",
+          "title": "Business overview for explicit period",
+          "question": "Дай взрослый бизнес-обзор {{bindings.main_organization}} за {{bindings.control_year}} год по данным 1С: обороты, входящие и исходящие деньги, нетто, НДС, долги, склад, клиенты, поставщики и что пока нельзя утверждать.",
+          "expected_intents": ["business_overview"],
+          "required_answer_shape": "direct_answer_first",
+          "forbidden_answer_patterns": [
+            "(?i)capability_id",
+            "(?i)selected_chain_id",
+            "(?i)runtime_",
+            "(?i)business_overview_route_template_v1"
+          ]
+        },
+        {
+          "step_id": "step_02_money_followup",
+          "title": "Money follow-up",
+          "question": "Раскрой деньги подробнее: сколько получили, сколько заплатили, какой чистый денежный поток, кто главный клиент и главный поставщик в {{bindings.control_year}}.",
+          "depends_on": ["step_01_business_overview"],
+          "required_answer_shape": "direct_answer_first"
+        },
+        {
+          "step_id": "step_03_best_year_all_time",
+          "title": "All-time best operating-flow year",
+          "question": "А если смотреть за все доступное время, какой самый доходный год по подтвержденным оборотам и почему? Не называй это бухгалтерской прибылью, если чистой прибыли нет.",
+          "depends_on": ["step_02_money_followup"],
+          "required_answer_shape": "direct_answer_first"
+        },
+        {
+          "step_id": "step_04_vat_explicit_period",
+          "title": "VAT explicit period",
+          "question": "Что с НДС за {{bindings.control_year}} год по {{bindings.main_organization}}: какая позиция видна, на чем она основана и чего не хватает для налогового вывода?",
+          "depends_on": ["step_03_best_year_all_time"],
+          "required_answer_shape": "direct_answer_first"
+        },
+        {
+          "step_id": "step_05_all_time_no_vat_carryover",
+          "title": "All-time reset without stale VAT carryover",
+          "question": "Теперь за все доступное время дай обзор компании в целом, но не тащи НДС за {{bindings.control_year}} как подтвержденную общую налоговую позицию.",
+          "depends_on": ["step_04_vat_explicit_period"],
+          "required_answer_shape": "direct_answer_first"
+        }
+      ]
+    },
+    {
+      "scenario_id": "agentic_loop_counterparty_pivot_control",
+      "title": "Counterparty pivot and legacy canaries",
+      "description": "Checks explicit counterparty arbitration after organization context and keeps technical/debug details out of the final answer.",
+      "steps": [
+        {
+          "step_id": "step_01_svk_money",
+          "title": "Explicit counterparty money flow",
+          "question": "Теперь отдельно по контрагенту {{bindings.svk_counterparty}}: сколько денег прошло, что входящее, что исходящее и есть ли документы или движения, на которых это основано?",
+          "expected_intents": ["value_flow"],
+          "required_answer_shape": "direct_answer_first",
+          "forbidden_answer_patterns": [
+            "(?i)capability_id",
+            "(?i)selected_chain_id",
+            "(?i)runtime_",
+            "(?i)mcp_discovery"
+          ]
+        },
+        {
+          "step_id": "step_02_svk_documents",
+          "title": "Counterparty documents follow-up",
+          "question": "Покажи документы по этой цепочке и не смешивай {{bindings.svk_counterparty}} с организацией {{bindings.main_organization}}.",
+          "depends_on": ["step_01_svk_money"],
+          "required_answer_shape": "direct_answer_first"
+        },
+        {
+          "step_id": "step_03_final_summary",
+          "title": "Final executive summary",
+          "question": "Собери короткий итог: что мы подтвердили по компании, что отдельно по {{bindings.svk_counterparty}}, какие выводы можно делать и какие нельзя.",
+          "depends_on": ["step_01_svk_money", "step_02_svk_documents"],
+          "required_answer_shape": "direct_answer_first"
+        }
+      ]
+    }
+  ]
+}

docs/orchestration/domain_scenario_loop_repo_adapter.md

@@ -145,7 +145,7 @@ It stores the GUI review under `artifacts/domain_runs/stage_agent_loops/<stage_i
 
 Use `python scripts/stage_agent_loop.py status --manifest docs/orchestration/<stage_loop>.json` as the cheap read-only checkpoint before continuing a stage. It prints the current next action, closing gate, latest GUI run, latest repair coder status, and latest repair validation status without modifying artifacts.
 
-Use `python scripts/stage_agent_loop.py continue --manifest docs/orchestration/<stage_loop>.json` as the safe one-command continuation layer. It can prepare a repair iteration and materialize `run-repair --dry-run` automatically; it will not run the real coder pass unless `--execute-repair` is passed, and it waits for a `--run-id assistant-stage1-<id>` when the next required step is post-repair rerun/ingest validation.
+Use `python scripts/stage_agent_loop.py continue --manifest docs/orchestration/<stage_loop>.json` as the safe one-command continuation layer. From a cold start it materializes `domain_pack_loop.command.txt` without launching the long live loop; after a GUI review it can prepare a repair iteration and materialize `run-repair --dry-run` automatically; it will not run the real coder pass unless `--execute-repair` is passed, and it waits for a `--run-id assistant-stage1-<id>` when the next required step is post-repair rerun/ingest validation.
 
 It also writes `stage_repair_handoff.md/json` next to the stage summary. That handoff is the preferred input for the next coder pass: it lists primary repair targets and sample user-facing failures without forcing the coder to reread the entire GUI conversation first.
 

docs/orchestration/stage_agent_loop_agentic_semantic_development_loop.json

@@ -0,0 +1,27 @@
+{
+  "schema_version": "stage_agent_loop_manifest_v1",
+  "stage_id": "agentic_semantic_development_loop",
+  "module_name": "Agentic Semantic Development Loop",
+  "title": "Agentic semantic development loop dogfood gate",
+  "architecture_phase": "turnaround_11_agentic_semantic_development_loop",
+  "agent_focus": "Automate stage implementation, semantic replay review, repair handoff, coder pass, rerun validation, and final human confirmation.",
+  "current_stage_status": "active_dogfood",
+  "global_plan_refs": [
+    "docs/orchestration/domain_scenario_loop_repo_adapter.md",
+    "docs/ARCH/11 - architecture_turnaround/README.md",
+    "AGENTS.md codex_domain_loop and agent_semantic_runs"
+  ],
+  "pack_manifest": "docs/orchestration/agentic_semantic_development_loop_stage_pack.json",
+  "loop_id": "agentic_semantic_development_loop",
+  "target_score": 88,
+  "max_iterations": 6,
+  "acceptance_invariants": [
+    "status command exposes next_action, repair state, validation state, and closing gate",
+    "continue command never runs the real coder pass without --execute-repair",
+    "patched repair cannot close the stage without successful rerun/ingest validation",
+    "business answers remain direct, context-aware, and free of internal route/debug ids",
+    "manual GUI confirmation remains required after accepted semantic replay"
+  ],
+  "save_autorun_on_accept": true,
+  "manual_confirmation_required_after_accept": true
+}

scripts/stage_agent_loop.py

@@ -1265,6 +1265,32 @@ def handle_continue(args: argparse.Namespace) -> int:
                     ),
                 }
             )
+    elif next_action == "run_stage_loop_or_ingest_gui_run":
+        if getattr(args, "run_id", None):
+            ingest_summary = ingest_gui_run_review(args)
+            payload.update(
+                {
+                    "performed_action": "ingest_gui_run_from_cold_start",
+                    "ingest_summary": ingest_summary,
+                    "next_action": ingest_summary.get("next_action"),
+                }
+            )
+        else:
+            write_json(stage_dir / "stage_manifest.json", stage_manifest)
+            write_text(stage_dir / "stage_manifest_source.txt", repo_relative(stage_manifest_path) + "\n")
+            command = build_domain_pack_loop_command(args, stage_manifest, stage_dir)
+            write_text(stage_dir / "domain_pack_loop.command.txt", " ".join(command) + "\n")
+            payload.update(
+                {
+                    "performed_action": "materialize_stage_run_dry_run",
+                    "domain_pack_loop_command": command,
+                    "next_action": next_action,
+                    "suggested_command": (
+                        "python scripts/stage_agent_loop.py run "
+                        "--manifest <stage_manifest.json>"
+                    ),
+                }
+            )
     else:
         payload.update(
             {

scripts/test_stage_agent_loop.py

@@ -778,6 +778,45 @@ class StageAgentLoopTests(unittest.TestCase):
         self.assertEqual(result["performed_action"], "wait_for_rerun_ingest")
         self.assertEqual(result["next_action"], "rerun_same_stage_or_gui_and_ingest_result")
 
+    def test_handle_continue_materializes_stage_run_from_cold_start(self) -> None:
+        with tempfile.TemporaryDirectory() as tmp:
+            root = Path(tmp)
+            manifest_path = root / "stage.json"
+            output_root = root / "stage_runs"
+            stage_dir = output_root / "agent_loop"
+            write_json(
+                manifest_path,
+                {
+                    "stage_id": "agent_loop",
+                    "module_name": "Agent Loop",
+                    "title": "Agent Loop",
+                    "pack_manifest": "docs/orchestration/demo_pack.json",
+                },
+            )
+
+            exit_code = stage_loop.handle_continue(
+                stage_args(
+                    manifest=str(manifest_path),
+                    output_root=str(output_root),
+                    handoff=None,
+                    iteration_id=None,
+                    plan=None,
+                    coder_schema=str(root / "coder.schema.json"),
+                    execute_repair=False,
+                    run_id=None,
+                    session_file=None,
+                    sessions_dir=str(root / "sessions"),
+                    reports_dir=str(root / "reports"),
+                    review_output_dir=None,
+                )
+            )
+            result = json.loads((stage_dir / "stage_continue_result.json").read_text(encoding="utf-8"))
+            command_text = (stage_dir / "domain_pack_loop.command.txt").read_text(encoding="utf-8")
+
+        self.assertEqual(exit_code, 0)
+        self.assertEqual(result["performed_action"], "materialize_stage_run_dry_run")
+        self.assertIn("run-pack-loop", command_text)
+
     def test_resolve_stage_repair_iteration_auto_prepares_from_handoff(self) -> None:
         with tempfile.TemporaryDirectory() as tmp:
             root = Path(tmp)