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debugger_terminate

End a GDB debugging session by specifying its session ID to stop program execution and release debugging resources.

Instructions

Terminate a debugging session.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • server.py:58-63 (handler)
    MCP tool handler for debugger_terminate - the entry point that receives the tool invocation and delegates to the debugger tools implementation
    @mcp.tool()
    def debugger_terminate(session_id: str) -> str:
        """Terminate a debugging session."""
        if not debugger_tools:
            return "Error: No debuggers are available on this system"
        return debugger_tools.terminate_session(session_id)
  • GDBTools.terminate_session - the tools-level implementation that wraps the session manager call with error handling and user-friendly messaging
    @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"
  • GDBSessionManager.terminate_session - the core implementation that exits the GDB controller process and removes it from the active sessions dictionary
    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 interface definition for terminate_session in DebuggerTools base class - defines the contract all debugger implementations must follow
    @abstractmethod
    def terminate_session(self, session_id: str) -> str:
        """Terminate a debugging session."""
        pass
  • server.py:58-63 (registration)
    Tool registration via @mcp.tool() decorator - registers debugger_terminate as an MCP tool that can be invoked by AI assistants
    @mcp.tool()
    def debugger_terminate(session_id: str) -> str:
        """Terminate a debugging session."""
        if not debugger_tools:
            return "Error: No debuggers are available on this system"
        return debugger_tools.terminate_session(session_id)
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. 'Terminate' implies a destructive action, but the description doesn't specify whether this is reversible, what happens to session data, if it requires specific permissions, or what the output contains. With an output schema present, some return details might be covered there, but the description adds minimal behavioral context beyond the basic action.

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 zero waste. It's front-loaded with the core action and resource, making it easy to parse. Every word earns its place, and there's no redundancy or 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 (simple termination action), one parameter, and the presence of an output schema, the description is minimally complete. It states what the tool does but lacks usage guidelines, behavioral details, or parameter context. With no annotations, it should do more to explain destructive implications, but the output schema may cover return values, keeping it at an adequate baseline.

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 description adds no parameter semantics beyond what the input schema provides. Schema description coverage is 0%, but the single parameter 'session_id' is self-explanatory from its title and required status. The description doesn't explain what a session_id is, how to obtain it, or format requirements. Baseline is 3 since the schema handles the parameter documentation adequately for this simple case.

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 'Terminate a debugging session' clearly states the action (terminate) and resource (debugging session) with a specific verb. It distinguishes from siblings like debugger_start or debugger_status by focusing on ending rather than initiating or checking status. However, it doesn't explicitly differentiate from gdb_terminate or lldb_terminate, which perform similar functions for different debuggers.

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. It doesn't mention prerequisites (e.g., needing an active session), exclusions, or when to choose debugger_terminate over gdb_terminate or lldb_terminate. The agent must infer usage from the name and context alone.

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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