get_cells

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

No annotations are provided, so the description must convey behavioral traits. It clearly indicates a read-only operation ('Read the current notebook state') and lists what is returned. It also discloses the dependency on an active browser connection, which is important for the agent to know.

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 two sentences, front-loading the core purpose and then adding a usage hint and prerequisite. Every sentence adds value, with no 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's simplicity (0 parameters, no annotations), the description covers the essential aspects: what it does, what it returns, when to use it, and a critical prerequisite. The output schema likely details the return structure, so the description adequately completes the picture.

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?

The input schema has zero parameters, so the description has no parameter burden. It provides context that the tool returns a list of cells, which is the key information for this read operation.

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 'Read the current notebook state: list of cells with their IDs, contents, and outputs' with a specific verb and resource. This distinguishes it from sibling tools like add_code_cell, run_code_cell, which are mutation operations.

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?

It explicitly says 'Essential for iterative work (write -> run -> read -> adjust)', indicating when this tool should be used. It also mentions the prerequisite of an active browser connection via open_colab_browser_connection, giving clear usage context.

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