feat!: Full code can now be generated by an external model and shared with the AI tool (Claude Code / Codex etc)!

model definitions now support a new `allow_code_generation` flag, only to be used with higher reasoning models such as GPT-5-Pro and-Gemini 2.5-Pro

 When `true`, the `chat` tool can now request the external model to generate a full implementation / update / instructions etc and then share the implementation with the calling agent.

 This effectively allows us to utilize more powerful models such as GPT-5-Pro to generate code for us or entire implementations (which are either API-only or part of the $200 Pro plan from within the ChatGPT app)

tools/shared/base_tool.py

@@ -17,6 +17,7 @@ from typing import TYPE_CHECKING, Any, Optional
 from mcp.types import TextContent
 
 if TYPE_CHECKING:
+    from providers.shared import ModelCapabilities
     from tools.models import ToolModelCategory
 
 from config import MCP_PROMPT_SIZE_LIMIT
@@ -165,6 +166,42 @@ class BaseTool(ABC):
         """
         pass
 
+    def get_capability_system_prompts(self, capabilities: Optional["ModelCapabilities"]) -> list[str]:
+        """Return additional system prompt snippets gated on model capabilities.
+
+        Subclasses can override this hook to append capability-specific
+        instructions (for example, enabling code-generation exports when a
+        model advertises support). The default implementation returns an empty
+        list so no extra instructions are appended.
+
+        Args:
+            capabilities: The resolved capabilities for the active model.
+
+        Returns:
+            List of prompt fragments to append after the base system prompt.
+        """
+
+        return []
+
+    def _augment_system_prompt_with_capabilities(
+        self, base_prompt: str, capabilities: Optional["ModelCapabilities"]
+    ) -> str:
+        """Merge capability-driven prompt addenda with the base system prompt."""
+
+        additions: list[str] = []
+        if capabilities is not None:
+            additions = [fragment.strip() for fragment in self.get_capability_system_prompts(capabilities) if fragment]
+
+        if not additions:
+            return base_prompt
+
+        addition_text = "\n\n".join(additions)
+        if not base_prompt:
+            return addition_text
+
+        suffix = "" if base_prompt.endswith("\n\n") else "\n\n"
+        return f"{base_prompt}{suffix}{addition_text}"
+
     def get_annotations(self) -> Optional[dict[str, Any]]:
         """
         Return optional annotations for this tool.
@@ -413,13 +450,16 @@ class BaseTool(ABC):
         for rank, canonical_name, capabilities in filtered[:limit]:
             details: list[str] = []
 
-            context_str = self._format_context_window(getattr(capabilities, "context_window", 0))
+            context_str = self._format_context_window(capabilities.context_window)
             if context_str:
                 details.append(context_str)
 
-            if getattr(capabilities, "supports_extended_thinking", False):
+            if capabilities.supports_extended_thinking:
                 details.append("thinking")
 
+            if capabilities.allow_code_generation:
+                details.append("code-gen")
+
             base = f"{canonical_name} (score {rank}"
             if details:
                 base = f"{base}, {', '.join(details)}"