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gdb_terminate

Stop a debugging session in GDB to end program analysis and free system resources.

Instructions

Terminate a GDB debugging session.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • server.py:88-94 (handler)
    MCP tool handler function 'gdb_terminate' decorated with @mcp.tool(). This is the main entry point that calls _get_gdb_tools().terminate_session(session_id).
    @mcp.tool()
    def gdb_terminate(session_id: str) -> str:
        """Terminate a GDB debugging session."""
        try:
            return _get_gdb_tools().terminate_session(session_id)
        except Exception as e:
            return f"Error: {str(e)}"
  • Concrete implementation of terminate_session in GDBTools class. Calls sessionManager.terminate_session(session_id) and returns success/error message with error handling via @handle_gdb_errors decorator.
    @handle_gdb_errors("terminating session")
    def terminate_session(self, session_id: str) -> str:
        if self.sessionManager.terminate_session(session_id):
            return f"GDB session '{session_id}' terminated successfully"
        return f"GDB session '{session_id}' not found"
  • Core session termination logic in GDBSessionManager. Terminates GDB process by calling gdb.exit(), removes session from dictionary, and returns True/False based on success.
    def terminate_session(self, session_id: str) -> bool:
        if session_id not in self.sessions:
            return False
        try:
            gdb = self.sessions[session_id]
            gdb.exit()
            del self.sessions[session_id]
            logger.info(f"Terminated GDB session: {session_id}")
            return True
        except Exception as e:
            logger.error(f"Failed to terminate GDB session: {e}")
            return False
  • Abstract method definition for terminate_session in DebuggerTools base class. Defines the interface contract that all debugger tool implementations must follow.
    @abstractmethod
    def terminate_session(self, session_id: str) -> str:
        """Terminate a debugging session."""
        pass
  • Factory method create_tools() that instantiates GDBTools with a GDBSessionManager. Called by _get_gdb_tools() in server.py to create the debugger tools instance.
    def create_tools(debugger_type: Optional[str] = None) -> Tuple[DebuggerTools, str]:
        """
        Create debugger tools.
        
        Args:
            debugger_type: 'gdb', 'lldb', or None for auto-detection
            
        Returns:
            Tuple of (tools, actual_debugger_type)
        """
        session_manager, actual_type = DebuggerFactory.create_session_manager(debugger_type)
        
        if actual_type == 'gdb':
            return GDBTools(session_manager), 'gdb'
        elif actual_type == 'lldb':
            return LLDBTools(session_manager), 'lldb'
        
        raise RuntimeError(f"Unknown debugger type: {actual_type}")
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Terminate' implies a destructive action, it does not specify effects like ending the session irreversibly, potential data loss, or required permissions. This leaves critical behavioral traits unclear for safe operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with no wasted words, making it highly concise and front-loaded. It efficiently communicates the core action without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (a destructive operation with no annotations), the description is minimal but adequate for basic understanding. The presence of an output schema reduces the need to explain return values, but more context on behavior and usage would improve completeness for safe agent operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, but the description adds no parameter semantics beyond what the schema implies (e.g., it does not explain what 'session_id' represents or its format). With one parameter and no schema details, the baseline is 3, as the description does not compensate for the coverage gap but doesn't worsen it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Terminate') and resource ('a GDB debugging session'), making the purpose evident. However, it does not explicitly differentiate from its sibling 'debugger_terminate' or 'lldb_terminate', which might cause confusion in tool selection without additional context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'debugger_terminate' or 'lldb_terminate', nor does it mention prerequisites such as requiring an active session. This lack of context could lead to incorrect tool invocation in a multi-debugger environment.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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