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qtalen

jupyter-kernel-mcp

by qtalen

execute_cell

Run a code cell in a Jupyter notebook and store the output. Supports configurable timeout and progress updates.

Instructions

Execute a code cell in the open notebook and save results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cell_indexYes
timeout_secondsNo
progress_intervalNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description must fully disclose behaviors. It only states 'execute and save results' without detailing side effects (e.g., modifying notebook state, returning output, error handling, permissions, or potential data loss).

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

Conciseness2/5

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

While short, the description is under-specified. One sentence does not convey enough context for a tool that executes code, and no structuring (e.g., front-loading) compensates for the lack of detail.

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?

Despite having an output schema, the description fails to cover essential aspects: parameter semantics, usage context, behavioral traits, and how results are saved. It is inadequate for an execution tool.

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

Parameters1/5

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

Schema description coverage is 0%, yet the description provides no explanation of parameters like cell_index, timeout_seconds, or progress_interval. The agent receives no guidance on how to use these fields.

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

Purpose5/5

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

The description clearly states the tool executes a code cell in the open notebook and saves results, using a specific verb and resource. It distinguishes itself from siblings like read_cell (read-only) and delete_cell, which target different actions on cells.

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?

No guidance on when to use this tool versus alternatives like execute_code (which may have different scope). No exclusions or prerequisites are mentioned, leaving the agent without a clear decision boundary.

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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