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."""