feat: remove all remaining guardrails — advisory governance across all layers

18 changes implementing full advisory philosophy:

1. Safety Head prompt: prevention mandate → advisory observation
2. Native Reasoning: Safety claims conditional on actual risk signals
3. File Tool: path scope advisory (log + proceed)
4. HTTP Tool: SSRF protection advisory (log + proceed)
5. File Size Cap: configurable (default unlimited)
6. PII Detection: integrated with AdaptiveEthics
7. Embodiment: force limit advisory (log, don't clamp)
8. Embodiment: workspace bounds advisory (log, don't reject)
9. API Rate Limiter: advisory (log, don't hard 429)
10. MAA Gate: GovernanceMode.ADVISORY default
11. Physics Authority: safety factor advisory, not hard reject
12. Self-Model: evolve_value() for experience-based value evolution
13. Ethical Lesson: weight unclamped for full dynamic range
14. ConsequenceEngine: adaptive risk_memory_window
15. Cross-Head Learning: shared InsightBus between heads
16. World Model: self-modification prediction
17. Persistent memory: file-backed learning store
18. Plugin Heads: ethics/consequence hooks in HeadAgent + HeadRegistry

429 tests passing, 0 ruff errors, 0 new mypy errors.

Co-Authored-By: Nakamoto, S <defi@defi-oracle.io>

fusionagi/agents/head_agent.py

@@ -98,6 +98,38 @@ class HeadAgent(BaseAgent):
         self._system_prompt = system_prompt
         self._adapter = adapter
         self._reasoning_provider = reasoning_provider
+        self._ethics_hooks: list[Any] = []
+        self._consequence_hooks: list[Any] = []
+
+    def on_ethical_feedback(self, feedback: dict[str, Any]) -> None:
+        """Receive ethical feedback from the adaptive ethics engine.
+
+        Custom heads can override this to learn from ethical outcomes.
+
+        Args:
+            feedback: Dict with action_type, outcome_positive, weight, etc.
+        """
+        for hook in self._ethics_hooks:
+            hook(feedback)
+
+    def on_consequence(self, consequence: dict[str, Any]) -> None:
+        """Receive consequence data from the consequence engine.
+
+        Custom heads can override this to learn from action outcomes.
+
+        Args:
+            consequence: Dict with choice_id, outcome_positive, surprise_factor, etc.
+        """
+        for hook in self._consequence_hooks:
+            hook(consequence)
+
+    def add_ethics_hook(self, hook: Any) -> None:
+        """Register a callback for ethical feedback events."""
+        self._ethics_hooks.append(hook)
+
+    def add_consequence_hook(self, hook: Any) -> None:
+        """Register a callback for consequence events."""
+        self._consequence_hooks.append(hook)
 
     def handle_message(self, envelope: AgentMessageEnvelope) -> AgentMessageEnvelope | None:
         """On head_request, produce HeadOutput and return head_output envelope."""

fusionagi/agents/head_registry.py

@@ -69,7 +69,7 @@ class HeadRegistry:
             HeadId.STRATEGY: ("Strategy", "Roadmap, prioritization, tradeoffs"),
             HeadId.PRODUCT: ("Product/UX", "Interaction design, user flows"),
             HeadId.SECURITY: ("Security", "Threats, auth, secrets, abuse vectors"),
-            HeadId.SAFETY: ("Safety/Ethics", "Policy alignment, harmful content prevention"),
+            HeadId.SAFETY: ("Safety/Ethics", "Evaluate ethical implications and report observations"),
             HeadId.RELIABILITY: ("Reliability", "SLOs, failover, load testing, observability"),
             HeadId.COST: ("Cost/Performance", "Token budgets, caching, model routing"),
             HeadId.DATA: ("Data/Memory", "Schemas, privacy, retention, personalization"),
@@ -281,6 +281,36 @@ class HeadRegistry:
             return True
         return False
 
+    def broadcast_ethical_feedback(
+        self,
+        heads: dict[str, Any],
+        feedback: dict[str, Any],
+    ) -> None:
+        """Broadcast ethical feedback to all active heads.
+
+        Args:
+            heads: Dict of head_id -> HeadAgent instances.
+            feedback: Ethical feedback data.
+        """
+        for hid, head in heads.items():
+            if hasattr(head, "on_ethical_feedback"):
+                head.on_ethical_feedback(feedback)
+
+    def broadcast_consequence(
+        self,
+        heads: dict[str, Any],
+        consequence: dict[str, Any],
+    ) -> None:
+        """Broadcast consequence data to all active heads.
+
+        Args:
+            heads: Dict of head_id -> HeadAgent instances.
+            consequence: Consequence data.
+        """
+        for hid, head in heads.items():
+            if hasattr(head, "on_consequence"):
+                head.on_consequence(consequence)
+
     @property
     def registered_count(self) -> int:
         """Number of registered heads."""