Method _on_tool_result

src/mcp_cli/chat/tool_processor.py:459–608

Callback when a tool completes. ENHANCED: Now includes value binding system for dataflow tracking. - Binds numeric results to $vN identifiers - Tracks per-tool call counts for anti-thrash - Caches results for state tracking

(self, result: CTPToolResult)

        await self.ui_manager.start_tool_execution(display_name, arguments)

    async def _on_tool_result(self, result: CTPToolResult) -> None:
        """Callback when a tool completes.

        ENHANCED: Now includes value binding system for dataflow tracking.
        - Binds numeric results to $vN identifiers
        - Tracks per-tool call counts for anti-thrash
        - Caches results for state tracking
        """
        meta = self._call_metadata.get(result.id)
        llm_tool_name = meta.llm_tool_name if meta else result.tool
        execution_tool_name = meta.execution_tool_name if meta else result.tool
        arguments = meta.arguments if meta else {}

        # For dynamic tools, extract the actual tool name for better logging/caching
        actual_tool_name = execution_tool_name
        actual_arguments = arguments
        if execution_tool_name == DYNAMIC_TOOL_PROXY_NAME and "tool_name" in arguments:
            actual_tool_name = arguments["tool_name"]
            actual_arguments = {k: v for k, v in arguments.items() if k != "tool_name"}

        success = result.is_success
        logger.info(
            f"Tool result ({actual_tool_name}): success={success}, error='{result.error}'"
        )

        tool_state = get_agent_tool_state(getattr(self.context, "agent_id", "default"))
        value_binding = None

        # Cache successful results and create value bindings
        if success and result.result is not None:
            # Extract the actual value from MCP response structure
            actual_result = self._extract_result_value(result.result)

            # Cache result for dedup
            tool_state.cache_result(actual_tool_name, actual_arguments, actual_result)
            logger.debug(f"Cached result for {actual_tool_name}: {actual_result}")

            # Create value binding ($v1, $v2, etc.) for dataflow tracking
            # Only bind "execution" tool results (not discovery tools)
            if not tool_state.is_discovery_tool(execution_tool_name):
                value_binding = tool_state.bind_value(
                    actual_tool_name, actual_arguments, actual_result
                )
                logger.info(
                    f"Bound value ${value_binding.id} = {actual_result} from {actual_tool_name}"
                )

            # Record numeric results for runaway detection
            if isinstance(actual_result, (int, float)):
                tool_state.record_numeric_result(float(actual_result))

        # Increment tool call counter for budget tracking (with tool name for split budgets)
        tool_state.increment_tool_call(execution_tool_name)

        # Record tool use for session-aware search boosting
        # Successful tools get boosted in future search results
        search_engine = get_search_engine()
        search_engine.record_tool_use(actual_tool_name, success=success)