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signal-slot

MCP GDB Server

by signal-slot

gdb_print

Print values of expressions during debugging sessions using the GDB interface. Evaluate variables or expressions in real-time to analyze and debug code efficiently.

Instructions

Print value of expression

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
expressionYesExpression to evaluate
sessionIdYesGDB 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. It states the action but lacks critical details: it doesn't specify that this requires an active GDB session (implied by sessionId but not explicit), describe output format (e.g., printed text or structured data), mention error handling (e.g., invalid expressions), or note side effects (e.g., potentially altering debug state). For a tool with no annotation coverage, this is a significant gap.

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, efficient sentence with zero waste—'Print value of expression' is front-loaded and directly conveys the core action. Every word earns its place, making it easy to parse quickly. No unnecessary details or redundancy are present, which is ideal for conciseness.

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

Completeness2/5

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

Given the complexity (a debugging tool with 2 required parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects (e.g., session requirements, output format), usage context, or error scenarios. For a tool in a suite like GDB where siblings involve session management and execution control, more guidance is needed to ensure the agent can use it correctly without trial and error.

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?

Schema description coverage is 100%, with both parameters (expression and sessionId) clearly documented in the schema. The description adds no additional meaning beyond the schema—it doesn't explain expression syntax (e.g., GDB expressions like '$rax'), sessionId usage (e.g., from gdb_list_sessions), or interactions between parameters. Given the high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but doesn't detract either.

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 'Print value of expression' clearly states the action (print) and target (expression value), making the purpose immediately understandable. It distinguishes from siblings like gdb_command (generic) or gdb_info_registers (specific), though it doesn't explicitly contrast them. The verb 'print' is specific enough for a debugging 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. It doesn't mention prerequisites (e.g., needing an active GDB session), differentiate from similar tools like gdb_examine (which might inspect memory), or specify use cases (e.g., evaluating variables during debugging). Without this, the agent must infer usage from 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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