Jupyter MCP Server

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

Annotations provide destructiveHint=true, indicating mutation, and the description adds valuable context beyond this: it discloses the return format ('diff style comparison') and specific behavior (e.g., '+ for new lines, - for deleted lines'). This enhances transparency about what the tool does and what to expect, though it doesn't cover aspects like error handling or prerequisites.

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

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

The description is front-loaded with the core action and includes essential behavioral details in just two sentences. Every sentence adds value: the first defines the purpose, and the second explains the return format, with no wasted words or redundancy.

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

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

Given the tool has annotations (destructiveHint), a rich input schema with 100% coverage, and an output schema (implied by 'Has output schema: true'), the description is complete enough. It covers the action, resource, and return behavior, addressing key aspects without needing to repeat structured data, making it well-rounded for this context.

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

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

Schema description coverage is 100%, with clear descriptions for both parameters (cell_index and cell_source). The description does not add any additional meaning or details about parameters beyond what the schema provides, such as format examples or constraints. Baseline score of 3 is appropriate as the schema adequately documents parameters.

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

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

The description clearly states the specific action ('overwrite the source of a specific cell') and resource ('from the currently activated notebook'), distinguishing it from siblings like delete_cell, insert_cell, or read_cell. It precisely defines what the tool does with a verb+resource+scope combination.

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

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

The description implies usage by specifying 'from the currently activated notebook,' suggesting it requires a notebook to be in use, but it does not explicitly state when to use this tool versus alternatives like insert_cell or read_cell. No explicit exclusions or named alternatives are provided, leaving usage context somewhat vague.

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