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notebook_state

Computes execution state for each notebook cell using execution counts and dependency edges.

Instructions

Compute best-effort execution state for each cell using execution_count + dependency edges.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
strip_outputsNo
include_markdownNo
Behavior2/5

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

No annotations exist, so description must cover behavioral traits. It mentions 'best-effort' but does not explain limitations, side effects, or resource usage. Mutation or read-only status is unclear.

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

Conciseness3/5

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

The single sentence is concise and front-loaded. However, it may be too brief for a tool with three parameters and no additional context.

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?

Lacking output schema and parameter details, the description fails to convey what the tool returns or how parameters affect results. Incomplete for effective use.

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%. The description does not explain the purpose or effect of any of the three parameters (path, strip_outputs, include_markdown).

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 computes execution state for each cell using execution_count and dependency edges. It distinguishes itself from sibling tools like notebook_analyze or jupyter_execute.

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 such as notebook_analyze or notebook_context. The description does not mention prerequisites or scenarios.

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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