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insert_cell

Destructive

Add code or markdown cells to Jupyter notebooks at specific positions to organize content and structure computational workflows.

Instructions

Insert a cell to specified position from the currently activated notebook.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cell_indexYesTarget index for insertion (0-based), use -1 to append at end
cell_typeYesType of cell to insert
cell_sourceYesSource content for the cell

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesSuccess message and the structure of its surrounding cells
Behavior3/5

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

Annotations already declare destructiveHint=true, indicating mutation. The description adds minimal behavioral context by specifying 'currently activated notebook', implying a dependency on prior state, but doesn't detail effects like shifting other cells, permissions needed, or error handling. With annotations covering the destructive nature, a 3 is appropriate for limited added value.

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 that front-loads the core action ('Insert a cell') and includes essential context ('to specified position from the currently activated notebook'). There is no wasted verbiage, making it highly concise and well-structured.

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

Completeness4/5

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

Given the tool's moderate complexity (mutation with 3 parameters), high schema coverage (100%), presence of annotations (destructiveHint), and an output schema (implied by context signals), the description is reasonably complete. It could improve by addressing sibling differentiation or error cases, but it covers the basic operation adequately.

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 clear documentation for all parameters (e.g., cell_index with -1 for appending, cell_type enum). The description adds no parameter-specific semantics beyond what the schema provides, so it meets the baseline of 3 without compensating for gaps.

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 clearly states the action ('Insert a cell') and the target ('currently activated notebook'), with the positional aspect ('to specified position') adding specificity. However, it doesn't explicitly differentiate from sibling tools like 'insert_execute_code_cell' or 'overwrite_cell_source', which would require a 5.

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 like 'insert_execute_code_cell' for code execution or 'overwrite_cell_source' for modifying existing cells. It mentions the context ('currently activated notebook') but lacks explicit when/when-not instructions or prerequisites.

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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