Implement ExerciseFormAiPromptContext and Refactor AI Prompt Job Functionality

- Introduced `ExerciseFormAiPromptContext` for unified handling of prompt-related data, enhancing the admin preview and exercise API.
- Added `run_exercise_form_ai_suggestion` function to streamline AI suggestion processing, integrating with the OpenRouter.
- Updated various modules to utilize the new context model, improving code clarity and reducing redundancy.
- Incremented application version to 0.8.162 and updated changelog to reflect these changes, including migration details and new functionality.

.claude/docs/technical/AI_PROMPT_TARGET_ARCHITECTURE.md

@@ -139,7 +139,7 @@ flowchart LR
 | Phase | Inhalt |
 |-------|--------|
 | **P0** | `AiPromptContextKind`, `load_ai_prompt_row` zentral; Übungs-KI über Laufzeit. |
-| **P1 (teilweise)** | `load_and_render_ai_prompt`, `AiPromptUnavailableError`, `render_ai_prompt_template_for_row`; **Pydantic** `ExerciseFormAiPromptContext` / `resolve_exercise_form_variables` in `ai_prompt_job` (Admin-Vorschau + gemeinsame Schnittstelle). Nächster Schritt: `POST /exercises/ai/suggest` kann dasselbe Kontextmodell nutzen; optionale `execute_*`-Fassade fuer OpenRouter-Schritt. |
+| **P1** | `load_and_render_ai_prompt`, `AiPromptUnavailableError`, `render_ai_prompt_template_for_row`; **`ExerciseFormAiPromptContext`** in `ai_prompt_context.py`; **`run_exercise_form_ai_suggestion`**; Übungs-API und Admin-Vorschau nutzen denselben Kontext. |
 | **P2** | Versionierung oder Audit-Spalten; **teilweise:** optionales OpenRouter-Modell pro Zeile (`openrouter_model`, Migration 070, Fallback `OPENROUTER_MODEL`); weitere Overrides (Temperatur) offen. |
 | **P3** | Composition/Segmente (JSON Schema Version 1) + UI nur für komplexe Slugs. |
 | **P4** | Erste Planungs-/Rahmen-Slugs mit dedizierten Buildern und Token-Budget-Strategien. |
@@ -159,7 +159,7 @@ flowchart LR
 - Ist-Implementierung Prompts/UI: `AI_PROMPT_SYSTEM_SPEC.md`
 - Zugriffsrecht Admin-Prompts: `ACCESS_LAYER_ENDPOINT_AUDIT.md`
 - Retrieval-Profile: `.claude/docs/working/AI_SKILL_RETRIEVAL_PROFILES_SPEC.md`
-- Übungs-KI-Codepfad: `backend/exercise_ai.py`, `backend/prompt_resolver.py`, `backend/ai_prompt_runtime.py`, `backend/ai_prompt_job.py`
+- Übungs-KI-Codepfad: `backend/exercise_ai.py`, `backend/prompt_resolver.py`, `backend/ai_prompt_runtime.py`, `backend/ai_prompt_context.py`, `backend/ai_prompt_job.py`
 
 ---
 

backend/ai_prompt_context.py

@@ -0,0 +1,86 @@
+"""
+Gemeinsame Pydantic-Modelle fuer Uebungs-KI-Kontext (Formularfelder → Prompt-Platzhalter).
+
+Keine Imports aus exercise_ai — vermeidet Zirkelimporte mit ai_prompt_job / exercise_ai.
+"""
+from __future__ import annotations
+
+from typing import List, Optional, Sequence, Tuple
+
+from pydantic import BaseModel, Field
+
+
+class ExerciseFormAiFocusRow(BaseModel):
+    """Fokusbereich fuer Skill-Retrieval (ai_skill_retrieval_profiles)."""
+
+    focus_area_id: int = Field(..., ge=1)
+    is_primary: Optional[bool] = False
+
+
+class ExerciseFormAiPromptContext(BaseModel):
+    """
+    Inhaltliche Eingabe fuer Uebungs-Prompts (Kurzfassung / Skill-Vorschlaege).
+
+    Wird genutzt von Admin-Prompt-Vorschau und POST /exercises/ai/suggest (via Mapping).
+    """
+
+    title: Optional[str] = ""
+    goal: Optional[str] = None
+    execution: Optional[str] = None
+    focus_hint: Optional[str] = None
+    focus_areas_context: Optional[List[ExerciseFormAiFocusRow]] = None
+
+    def focus_area_tuples(self) -> Optional[List[Tuple[int, bool]]]:
+        if not self.focus_areas_context:
+            return None
+        return [(int(x.focus_area_id), bool(x.is_primary)) for x in self.focus_areas_context]
+
+    @classmethod
+    def from_api_suggest(
+        cls,
+        *,
+        title: Optional[str] = None,
+        goal: Optional[str] = None,
+        execution: Optional[str] = None,
+        focus_area_hint: Optional[str] = None,
+        focus_areas_context: Optional[Sequence[ExerciseFormAiFocusRow]] = None,
+    ) -> ExerciseFormAiPromptContext:
+        """Mappt Felder aus POST /exercises/ai/suggest (focus_area_hint → focus_hint)."""
+        hint = (focus_area_hint or "").strip() or None
+        return cls(
+            title=(title or "").strip(),
+            goal=goal,
+            execution=execution,
+            focus_hint=hint,
+            focus_areas_context=list(focus_areas_context) if focus_areas_context else None,
+        )
+
+    @classmethod
+    def from_focus_tuples(
+        cls,
+        *,
+        title: str = "",
+        goal: Optional[str] = None,
+        execution: Optional[str] = None,
+        focus_hint: Optional[str] = None,
+        focus_tuples: Optional[Sequence[Tuple[int, bool]]] = None,
+    ) -> ExerciseFormAiPromptContext:
+        rows = None
+        if focus_tuples:
+            rows = [
+                ExerciseFormAiFocusRow(focus_area_id=int(fid), is_primary=bool(prim))
+                for fid, prim in focus_tuples
+            ]
+        return cls(
+            title=(title or "").strip(),
+            goal=goal,
+            execution=execution,
+            focus_hint=(focus_hint or "").strip() or None,
+            focus_areas_context=rows,
+        )
+
+
+__all__ = [
+    "ExerciseFormAiFocusRow",
+    "ExerciseFormAiPromptContext",
+]

backend/ai_prompt_job.py

@@ -1,47 +1,16 @@
 """
-KI-Prompt Jobs: validierter Kontext (Pydantic) + Zugriff auf gemeinsame Resolver.
+KI-Prompt Jobs: Resolver + oeffentliche Fassade fuer Uebungs-KI-Aufrufe.
 
-Importiert exercise_ai nur fuer Platzhalter-Builder — Router importieren dieses Modul oder exercise_ai,
+Importiert exercise_ai fuer Platzhalter-Builder und OpenRouter-Orchestrierung.
-nicht umgekehrt von exercise_ai nach ai_prompt_job (Zirkel vermeiden).
 """
 from __future__ import annotations
 
-from typing import Dict, List, Optional, Tuple
+from typing import Any, Dict
-
-from pydantic import BaseModel, Field
 
+from ai_prompt_context import ExerciseFormAiFocusRow, ExerciseFormAiPromptContext
 from exercise_ai import build_exercise_placeholder_variables
 
 
-class ExerciseFormAiFocusRow(BaseModel):
-    """Fokusbereich fuer Skill-Retrieval-Kontext (wie ExerciseAiFocusCtx / Admin-Preview)."""
-
-    focus_area_id: int = Field(..., ge=1)
-    is_primary: Optional[bool] = False
-
-
-class ExerciseFormAiPromptContext(BaseModel):
-    """
-    Eingabe fuer Uebungsbezogene Prompts (Kurzfassung / Skill-JSON-Vorschlag).
-    Entspricht fachlich dem Preview-Body unter /api/admin/ai-prompts/*/preview.
-
-    Abgrenzung: POST /exercises/ai/suggest nutzt ExerciseAiSuggestBody mit include_summary /
-    include_skills usw.; dieses Modell bildet nur die gemeinsamen Formularfelder — wie die
-    Admin-Vorschau-Body (AiPromptPreviewBody).
-    """
-
-    title: Optional[str] = ""
-    goal: Optional[str] = None
-    execution: Optional[str] = None
-    focus_hint: Optional[str] = None
-    focus_areas_context: Optional[List[ExerciseFormAiFocusRow]] = None
-
-    def focus_area_tuples(self) -> Optional[List[Tuple[int, bool]]]:
-        if not self.focus_areas_context:
-            return None
-        return [(int(x.focus_area_id), bool(x.is_primary)) for x in self.focus_areas_context]
-
-
 def resolve_exercise_form_variables(cur, slug: str, ctx: ExerciseFormAiPromptContext) -> Dict[str, str]:
     """Baut die Mustache-Map fuer exercise_summary / exercise_skill_suggestions."""
     return build_exercise_placeholder_variables(
@@ -55,8 +24,31 @@ def resolve_exercise_form_variables(cur, slug: str, ctx: ExerciseFormAiPromptCon
     )
 
 
+def run_exercise_form_ai_suggestion(
+    cur,
+    ctx: ExerciseFormAiPromptContext,
+    *,
+    want_summary: bool,
+    want_skills: bool,
+) -> Dict[str, Any]:
+    """
+    Fuehrt Uebungs-KI aus (OpenRouter) — ein Einstieg fuer Router und kuenftige Jobs.
+
+    ``ctx`` = Formularinhalt; ``want_*`` = welche Prompt-Slugs angefragt werden.
+    """
+    from exercise_ai import run_exercise_ai_suggestion
+
+    return run_exercise_ai_suggestion(
+        cur,
+        form_ctx=ctx,
+        want_summary=want_summary,
+        want_skills=want_skills,
+    )
+
+
 __all__ = [
     "ExerciseFormAiFocusRow",
     "ExerciseFormAiPromptContext",
     "resolve_exercise_form_variables",
+    "run_exercise_form_ai_suggestion",
 ]

backend/exercise_ai.py

@@ -24,6 +24,7 @@ from openrouter_chat import (
     openrouter_chat_completion,
 )
 
+from ai_prompt_context import ExerciseFormAiPromptContext
 from ai_prompt_runtime import AiPromptUnavailableError, load_and_render_ai_prompt
 
 _LOGGER = logging.getLogger("shinkan.exercise_ai")
@@ -682,16 +683,18 @@ def _require_openrouter_key() -> str:
 def run_exercise_ai_suggestion(
     cur,
     *,
-    title: Optional[str],
+    form_ctx: ExerciseFormAiPromptContext,
-    goal: Optional[str],
-    execution: Optional[str],
-    focus_area_hint: Optional[str],
-    focus_areas_context: Optional[Sequence[Tuple[int, bool]]] = None,
     want_summary: bool,
     want_skills: bool,
 ) -> Dict[str, Any]:
     key = _require_openrouter_key()
 
+    title = form_ctx.title
+    goal = form_ctx.goal
+    execution = form_ctx.execution
+    focus_area_hint = form_ctx.focus_hint
+    focus_areas_context = form_ctx.focus_area_tuples()
+
     g_plain = strip_html_to_plain(goal)
     e_plain = strip_html_to_plain(execution)
     if not (g_plain.strip() or e_plain.strip()):

backend/routers/ai_prompts_admin.py

@@ -12,7 +12,8 @@ from pydantic import BaseModel, Field
 
 from auth import require_auth
 from club_tenancy import is_superadmin
-from ai_prompt_job import ExerciseFormAiPromptContext, resolve_exercise_form_variables
+from ai_prompt_context import ExerciseFormAiPromptContext
+from ai_prompt_job import resolve_exercise_form_variables
 from ai_prompt_runtime import render_ai_prompt_template_for_row
 from db import get_cursor, get_db, r2d
 from prompt_resolver import exercise_placeholder_catalog
@@ -60,17 +61,8 @@ class AiPromptUpdateBody(BaseModel):
     openrouter_model: Optional[str] = Field(None, max_length=200)
 
 
-class AiPromptPreviewFocus(BaseModel):
+class AiPromptPreviewBody(ExerciseFormAiPromptContext):
-    focus_area_id: int = Field(..., ge=1)
+    """Preview-POST: gleiche Felder wie ExerciseFormAiPromptContext (focus_hint, nicht focus_area_hint)."""
-    is_primary: Optional[bool] = False
-
-
-class AiPromptPreviewBody(BaseModel):
-    title: Optional[str] = ""
-    goal: Optional[str] = None
-    execution: Optional[str] = None
-    focus_hint: Optional[str] = None
-    focus_areas_context: Optional[List[AiPromptPreviewFocus]] = None
 
 
 @router.get("/api/admin/ai-prompts/catalog/placeholders")
@@ -228,8 +220,7 @@ def preview_ai_prompt(prompt_id: int, body: AiPromptPreviewBody, session: dict =
         warn: Optional[str] = None
         if slug in ("exercise_summary", "exercise_skill_suggestions"):
             try:
-                pf_ctx = ExerciseFormAiPromptContext.model_validate(body.model_dump())
+                vars_map = resolve_exercise_form_variables(cur, slug, body)
-                vars_map = resolve_exercise_form_variables(cur, slug, pf_ctx)
             except ValueError as e:
                 raise HTTPException(status_code=400, detail=str(e)) from e
         elif slug == "pipeline":

backend/routers/exercises.py

@@ -35,7 +35,8 @@ from tenant_context import TenantContext, get_tenant_context, get_tenant_context
 from media_storage import get_effective_media_root, library_storage_key, path_under_media_root
 from media_rights import assert_rights_for_exercise_link, validate_rights_declaration, write_rights_declaration, update_rights_quick_fields
 from media_legal_hold import assert_not_under_legal_hold
-from exercise_ai import run_exercise_ai_suggestion
+from ai_prompt_context import ExerciseFormAiFocusRow, ExerciseFormAiPromptContext
+from ai_prompt_job import run_exercise_form_ai_suggestion
 
 from exercise_rich_text import (
     RICH_HTML_EXERCISE_FIELDS,
@@ -358,11 +359,8 @@ class ExerciseMediaFromAsset(BaseModel):
     media_type: Optional[str] = None
 
 
-class ExerciseAiFocusCtx(BaseModel):
+class ExerciseAiFocusCtx(ExerciseFormAiFocusRow):
-    """Fokusbereich fuer Skill-Kataloggewichte (Migration 068 ai_skill_retrieval_profiles)."""
+    """Alias fuer OpenAPI — identisch zu ExerciseFormAiFocusRow."""
-
-    focus_area_id: int = Field(..., ge=1)
-    is_primary: Optional[bool] = False
 
 
 class ExerciseAiSuggestBody(BaseModel):
@@ -370,7 +368,7 @@ class ExerciseAiSuggestBody(BaseModel):
     goal: Optional[str] = Field(None, max_length=64000)
     execution: Optional[str] = Field(None, max_length=128000)
     focus_area_hint: Optional[str] = Field(None, max_length=1200)
-    focus_areas_context: Optional[list[ExerciseAiFocusCtx]] = Field(
+    focus_areas_context: Optional[list[ExerciseFormAiFocusRow]] = Field(
         None,
         description="Optionale Reihenfolge Primär zuerst; steuert Katalogpriorisierung",
     )
@@ -383,6 +381,15 @@ class ExerciseAiSuggestBody(BaseModel):
             raise ValueError("Mindestens include_summary oder include_skills aktivieren.")
         return self
 
+    def to_form_context(self) -> ExerciseFormAiPromptContext:
+        return ExerciseFormAiPromptContext.from_api_suggest(
+            title=self.title,
+            goal=self.goal,
+            execution=self.execution,
+            focus_area_hint=self.focus_area_hint,
+            focus_areas_context=self.focus_areas_context,
+        )
+
 
 class ExerciseAiRegenerateBody(BaseModel):
     """Welche Artefakte neu angefragt werden sollen."""
@@ -2306,17 +2313,9 @@ def exercise_ai_suggest_endpoint(
     _ = tenant.profile_id
     with get_db() as conn:
         cur = get_cursor(conn)
-        fctx = None
+        payload = run_exercise_form_ai_suggestion(
-        if body.focus_areas_context:
-            fctx = [(x.focus_area_id, bool(x.is_primary)) for x in body.focus_areas_context]
-
-        payload = run_exercise_ai_suggestion(
             cur,
-            title=(body.title or "").strip(),
+            body.to_form_context(),
-            goal=body.goal,
-            execution=body.execution,
-            focus_area_hint=(body.focus_area_hint or "").strip() or None,
-            focus_areas_context=fctx,
             want_summary=body.include_summary,
             want_skills=body.include_skills,
         )
@@ -2344,13 +2343,16 @@ def exercise_ai_regenerate_endpoint(
         focus = _focus_area_hint_from_detail(exercise)
         fctx = _focus_areas_ai_ctx_from_detail(exercise)
 
-        payload = run_exercise_ai_suggestion(
+        ctx = ExerciseFormAiPromptContext.from_focus_tuples(
-            cur,
             title=str(exercise.get("title") or "").strip(),
             goal=exercise.get("goal"),
             execution=exercise.get("execution"),
-            focus_area_hint=focus or None,
+            focus_hint=focus or None,
-            focus_areas_context=fctx or None,
+            focus_tuples=fctx or None,
+        )
+        payload = run_exercise_form_ai_suggestion(
+            cur,
+            ctx,
             want_summary=want_summary,
             want_skills=want_skills,
         )

backend/version.py

@@ -1,6 +1,6 @@
 # Shinkan Jinkendo Version Information
 
-APP_VERSION = "0.8.161"
+APP_VERSION = "0.8.162"
 BUILD_DATE = "2026-05-31"
 DB_SCHEMA_VERSION = "20260531070"
 
@@ -20,13 +20,14 @@ MODULE_VERSIONS = {
     "media_lifecycle": "1.1.0",  # P-11: Retention-Job ueberspringt Legal-Hold-Assets
     "admin_ai_skill_retrieval": "1.0.0",  # Superadmin CRUD /api/admin/ai-skill-retrieval-profiles (Migration 068)
     "admin_ai_prompts": "1.0.3",  # Migration 070: openrouter_model; PUT/Liste/Detail
-    "ai_prompt_job": "0.1.0",  # ExerciseFormAiPromptContext, resolve_exercise_form_variables — P1 Kontext-Schnittstelle
+    "ai_prompt_job": "0.2.0",  # run_exercise_form_ai_suggestion; Kontext in ai_prompt_context
+    "ai_prompt_context": "0.1.0",  # ExerciseFormAiPromptContext — Formularfelder fuer Uebungs-Prompts
     "ai_prompt_runtime": "0.2.0",  # load_and_render_ai_prompt, AiPromptUnavailableError, render_ai_prompt_template_for_row
     "groups": "0.1.0",
     "skills": "0.1.1",  # DB 065 karate_relevance + relevance_level; CRUD unterstützt Felder
     "skill_profiles": "1.0.0",  # Phase 3: gewichtetes Fähigkeiten-Profil + skill-discovery/suggestions
     "methods": "0.1.0",
-    "exercises": "2.31.3",  # exercise_ai: OpenRouter-Modell pro Prompt-Slug; Response models_by_slug
+    "exercises": "2.31.4",  # ai/suggest + regenerate: ExerciseFormAiPromptContext via run_exercise_form_ai_suggestion
     "training_units": "0.4.0",  # POST .../publish-to-framework: Ablauf aus geplanter Einheit → Rahmen-Slot-Blueprint
     "training_programs": "0.1.0",
     "planning": "0.15.0",  # Vorlagen: Strukturvorschau, Bearbeiten inkl. Split-Sessions + Beschreibung
@@ -41,6 +42,14 @@ MODULE_VERSIONS = {
 }
 
 CHANGELOG = [
+    {
+        "version": "0.8.162",
+        "date": "2026-05-31",
+        "changes": [
+            "KI Prompt P1 abgeschlossen: ai_prompt_context (Formular-Kontext), run_exercise_form_ai_suggestion als gemeinsamer Einstieg;",
+            "POST /exercises/ai/suggest und regenerate bauen ExerciseFormAiPromptContext; Admin-Vorschau nutzt dasselbe Modell.",
+        ],
+    },
     {
         "version": "0.8.161",
         "date": "2026-05-31",

docs/HANDOVER.md

@@ -1,7 +1,7 @@
 # Shinkan Jinkendo – Entwicklungsstand & Handover
 
-**Stand:** 2026-05-30  
+**Stand:** 2026-05-31  
-**App-Version / DB-Schema:** App **`0.8.160`** (u. a. KI Prompt P1: `load_and_render_ai_prompt`, `ai_prompt_job`); Zielarchitektur-Doku weiterhin **`.claude/docs/technical/AI_PROMPT_TARGET_ARCHITECTURE.md`**. DB: maßgeblich **`backend/version.py`** → `APP_VERSION`, `DB_SCHEMA_VERSION` (aktuell `20260530069`).
+**App-Version / DB-Schema:** App **`0.8.162`** (KI Prompt P1: gemeinsamer Formular-Kontext `ExerciseFormAiPromptContext`, `run_exercise_form_ai_suggestion`); Zielarchitektur **`.claude/docs/technical/AI_PROMPT_TARGET_ARCHITECTURE.md`**. DB: **`backend/version.py`** → `DB_SCHEMA_VERSION` (aktuell `20260531070`).
 
 Diese Datei ist die **Einstiegs-Doku für neue Chat-Sessions**: Anforderungen im Detail stehen in `.claude/docs/` (siehe unten); hier der **implementierte Stand**, **Medien-Meilenstein** und **sinnvolle nächste Schritte**.
 
@@ -89,12 +89,12 @@ Das Schema ist gegenüber dem Code zurück: Migration **`022_skills_schema_compl
 - **Varianten:** Speichern in der **Aktionsleiste** persistiert zuerst geänderte Varianten (`persistPendingVariantChanges`), dann Übungs-Stammdaten; „Variante anlegen“ als `type="button"` ohne verschachteltes Formular (`createVariantFromDraft`)
 - **Governance (Übungen):** Owner = `created_by`; Bearbeiten = Ersteller, Plattform-Admin oder `can_plan_in_club` bei `visibility=club`; Löschen `club` = nur `club_admin`; Details **`FEATURES_DELIVERED_2026-Q2.md`** §16, **`EXERCISES_API_SPEC.md`** Permissions
 
-### 2.8 KI Assistenz Übungen & Skill-Katalog-Retrieval (Stand **0.8.160**)
+### 2.8 KI Assistenz Übungen & Skill-Katalog-Retrieval (Stand **0.8.162**)
 
 - **Zielarchitektur (Pflicht fuer Erweiterungen):** `.claude/docs/technical/AI_PROMPT_TARGET_ARCHITECTURE.md` — Kontext-Arten, Composition, Einbindung Planung/Rahmen; Phasenplan P0–P4.
 - **Doku:** Umsetzung `.claude/docs/working/AI_EXERCISE_IMPLEMENTATION_PLAN.md`; Profil-/JSON-Konzept `.claude/docs/working/AI_SKILL_RETRIEVAL_PROFILES_SPEC.md`; Ist-Prompt/UI **`AI_PROMPT_SYSTEM_SPEC.md`**; API-Felder **`KI_FEATURES_SPEC.md`** §5.2  
-- **Runtime / Job:** **`ai_prompt_runtime`** (`load_and_render_ai_prompt`, `AiPromptUnavailableError`, Rendern aus DB-Zeile fuer Vorschau); **`ai_prompt_job`** — Pydantic **`ExerciseFormAiPromptContext`**, **`resolve_exercise_form_variables`** (Admin-Preview + Schnittstelle fuer weitere Router); **`exercise_ai`** laedt/rendert ueber Laufzeit und ruft OpenRouter  
+- **Kontext / Job:** **`ai_prompt_context`** — **`ExerciseFormAiPromptContext`** (Titel, Ziel, Durchführung, Fokus — ein Modell fuer Admin-Vorschau und Übungs-API); **`ai_prompt_job`** — **`run_exercise_form_ai_suggestion`**, **`resolve_exercise_form_variables`**; **`ai_prompt_runtime`** — Laden/Rendern aus DB; **`exercise_ai`** — OpenRouter nach Rendern  
-- **DB:** Migration **`067`** **`ai_prompts`** (Slug **`exercise_summary`**, **`exercise_skill_suggestions`** — müssen **aktiv** sein); Migration **`069`** setzt **`default_template`** wo leer; Migration **`068`** **`ai_skill_retrieval_profiles`** (Seed Standard + ggf. Gewaltschutz-Fokus)  
+- **DB:** Migration **`067`** **`ai_prompts`**; **`069`** **`default_template`**; **`068`** **`ai_skill_retrieval_profiles`**; **`070`** **`openrouter_model`** (optional pro Prompt, Fallback **`OPENROUTER_MODEL`**)  
 - **`exercise_ai`:** Gewichtungen, Kategorie‑Anteil‑Caps (~Token), Keyword-Patches aus Ziel/Durchführung (z. B. Rollenspiel vs. Befreiung/Haltegriff)  
 - **API:** `POST /api/exercises/ai/suggest` optional **`focus_areas_context`**; **`POST …/ai/regenerate`** nutzt gespeicherte `exercise_focus_areas` — **Pflege:** Superadmin **`/api/admin/ai-skill-retrieval-profiles*`** (`routers/ai_skill_retrieval_admin.py`), **`/api/admin/ai-prompts*`** (`routers/ai_prompts_admin.py`), UI **`/admin/ai-prompts`**  
 - **Diagnose bei leerem Dialog / Fehlern:** Umgebungsvariable **`SHINKAN_AI_DEBUG=1`** auf der API; in den Logs dann **`AI_DEBUG`** (`shinkan.exercise_ai`) und **`[AI_DEBUG/openrouter]`** (`shinkan.openrouter`) mit Prompt-Längen, Token-Zahlen und ggf. JSON-Parse-Anfang