feat(05-01): AgentTemplate ORM model, migration 007, and system prompt builder

- Add AgentTemplate ORM model to tenant.py (global, not tenant-scoped)
- Create migration 007 with agent_templates table and 7 seed templates
- Create shared/prompts/system_prompt_builder.py with build_system_prompt()
- AI transparency clause always present (non-negotiable per Phase 1 decision)
- Unit tests pass (17 tests, all sections verified)

packages/shared/shared/models/tenant.py

@@ -186,6 +186,89 @@ class Agent(Base):
         return f"<Agent id={self.id} name={self.name!r} tenant_id={self.tenant_id}>"
 
 
+class AgentTemplate(Base):
+    """
+    Pre-built AI employee templates available to all tenants.
+
+    Templates are NOT tenant-scoped (no tenant_id, no RLS). Any authenticated
+    portal user can browse templates. Only tenant admins can deploy them.
+    Deploying a template creates an independent Agent snapshot — subsequent
+    changes to the template do not affect deployed agents.
+    """
+
+    __tablename__ = "agent_templates"
+
+    id: Mapped[uuid.UUID] = mapped_column(
+        UUID(as_uuid=True),
+        primary_key=True,
+        default=uuid.uuid4,
+    )
+    name: Mapped[str] = mapped_column(String(255), nullable=False)
+    role: Mapped[str] = mapped_column(String(255), nullable=False)
+    description: Mapped[str] = mapped_column(
+        Text,
+        nullable=False,
+        default="",
+        comment="2-3 sentence card preview description shown in the template gallery",
+    )
+    category: Mapped[str] = mapped_column(
+        String(100),
+        nullable=False,
+        default="general",
+        comment="Template category: support | sales | operations | finance | general",
+    )
+    persona: Mapped[str] = mapped_column(
+        Text,
+        nullable=False,
+        default="",
+        comment="Paragraph describing the agent's communication style and personality",
+    )
+    system_prompt: Mapped[str] = mapped_column(
+        Text,
+        nullable=False,
+        default="",
+        comment="Full system prompt including AI transparency clause",
+    )
+    model_preference: Mapped[str] = mapped_column(
+        String(50),
+        nullable=False,
+        default="quality",
+        comment="quality | balanced | economy | local",
+    )
+    tool_assignments: Mapped[list[Any]] = mapped_column(
+        JSON,
+        nullable=False,
+        default=list,
+        comment="JSON array of tool name strings",
+    )
+    escalation_rules: Mapped[list[Any]] = mapped_column(
+        JSON,
+        nullable=False,
+        default=list,
+        comment="JSON array of {condition, action} escalation rule objects",
+    )
+    is_active: Mapped[bool] = mapped_column(
+        Boolean,
+        nullable=False,
+        default=True,
+        comment="Inactive templates are hidden from the gallery",
+    )
+    sort_order: Mapped[int] = mapped_column(
+        Integer,
+        nullable=False,
+        default=0,
+        comment="Display order in the template gallery (ascending)",
+    )
+    created_at: Mapped[datetime] = mapped_column(
+        DateTime(timezone=True),
+        nullable=False,
+        server_default=func.now(),
+    )
+
+    def __repr__(self) -> str:
+        return f"<AgentTemplate id={self.id} name={self.name!r} category={self.category!r}>"
+
+
 class ChannelConnection(Base):
     """
     Links a messaging platform workspace to a Konstruct tenant.

packages/shared/shared/prompts/__init__.py

@@ -0,0 +1 @@
+# Konstruct system prompt utilities

packages/shared/shared/prompts/system_prompt_builder.py

@@ -0,0 +1,68 @@
+"""
+System prompt builder for Konstruct AI employees.
+
+Assembles a coherent system prompt from wizard inputs (name, role, persona,
+tools, escalation rules) and always appends the mandatory AI transparency
+clause. The transparency clause is non-negotiable and cannot be omitted.
+"""
+
+from __future__ import annotations
+
+# Non-negotiable AI transparency clause (Phase 1 architectural decision).
+# Agents must always disclose their AI nature when directly asked.
+AI_TRANSPARENCY_CLAUSE = (
+    "When directly asked if you are an AI, always disclose that you are an AI assistant."
+)
+
+
+def build_system_prompt(
+    name: str,
+    role: str,
+    persona: str = "",
+    tool_assignments: list[str] | None = None,
+    escalation_rules: list[dict[str, str]] | None = None,
+) -> str:
+    """
+    Build a system prompt for an AI employee from wizard inputs.
+
+    Args:
+        name: The agent's display name (e.g. "Mara").
+        role: The agent's role title (e.g. "Customer Support Rep").
+        persona: Optional paragraph describing the agent's communication style
+                 and personality traits.
+        tool_assignments: Optional list of tool names available to the agent.
+                          Omitted from the prompt when empty or None.
+        escalation_rules: Optional list of escalation rule dicts, each with
+                          "condition" and "action" keys. Omitted when empty/None.
+
+    Returns:
+        A complete system prompt string, always ending with the AI transparency
+        clause.
+    """
+    sections: list[str] = []
+
+    # --- Identity header ---
+    identity = f"You are {name}, {role}."
+    if persona:
+        identity = f"{identity}\n\n{persona}"
+    sections.append(identity)
+
+    # --- Tools section (omitted when empty) ---
+    effective_tools = tool_assignments if tool_assignments else []
+    if effective_tools:
+        tool_lines = "\n".join(f"- {tool}" for tool in effective_tools)
+        sections.append(f"You have access to the following tools:\n{tool_lines}")
+
+    # --- Escalation rules section (omitted when empty) ---
+    effective_rules = escalation_rules if escalation_rules else []
+    if effective_rules:
+        rule_lines = "\n".join(
+            f"- If {rule.get('condition', '')}: {rule.get('action', '')}"
+            for rule in effective_rules
+        )
+        sections.append(f"Escalation rules:\n{rule_lines}")
+
+    # --- AI transparency clause (always present, non-negotiable) ---
+    sections.append(AI_TRANSPARENCY_CLAUSE)
+
+    return "\n\n".join(sections)