14 tools with complete schemas and descriptions, but significant quality gaps. All tools have input schemas with typed parameters and descriptions present. However, descriptions are often generic (10-50 chars) and lack actionable context for LLM selection. Tool names follow verb_noun convention well (start_debugging_session, set_breakpoint, get_stack_trace). No enum constraints on string parameters. Output schemas documented via Pydantic models but not exposed in tool definitions. Error handling present but minimal, no recovery guidance or categorization. Session-based architecture requires LLM to track session_id across calls, increasing cognitive load. No tool annotations (readOnlyHint/destructiveHint) despite clear read/write distinction in risk column.

• Expand tool descriptions to 100-200 chars. Add WHEN to use each tool: 'step_over: Execute the next line without entering function calls. Use when you want to skip function internals and focus on the current scope. Prefer over step_into when you trust the function logic.'
• Add enum constraints to string parameters. For set_breakpoint location, define: enum=['file:line', 'function_name', '*address'] or use a regex pattern in schema and document in description.
• Implement tool annotations in schema. Add destructiveHint=true to delete_breakpoint, set_variable, close_debugging_session. Add readOnlyHint=true to get_stack_trace, get_variable, list_breakpoints, evaluate_expression.
• Add a list_active_sessions() tool so LLMs can discover available sessions without relying on memory. Return session_id, binary_path, and status for each active session.
• Enhance error messages with recovery guidance. E.g., 'Invalid session ID: {session_id}. Active sessions: {list}. Call start_debugging_session() to create a new session or use an ID from the list above.'

Inferred effective spec: <=2025-11-25.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry