notebooklm_list_notebooks

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds two useful behavioral facts beyond the annotations: only 'active' notebooks are returned, and the response carries identifiers plus metadata. It does not discuss pagination, sorting, or what 'metadatos' contains, but with annotations carrying the safety burden a 3 is appropriate.

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?

A single front-loaded sentence with the verb first and no filler. Every clause (scope 'activos', source 'en Google NotebookLM', return payload) earns its place.

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?

With no output schema and no parameters, the description carries the full burden of describing the return shape, and it only gestures at 'metadatos' without listing fields. It is adequate for a simple list call but leaves the agent guessing what metadata keys to expect.

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 tool takes zero parameters and schema coverage is 100%, so there is nothing for the description to disambiguate. Baseline 4 applies for a parameterless tool.

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?

States a specific verb ('Lista') and a precise resource ('cuadernos de investigación jurídica activos en Google NotebookLM'), and it names the return payload (notebook_id y metadatos). It is clearly the read/list member of the notebooklm_* family, distinguishable from create/add_source/query by the verb alone, though it never explicitly contrasts itself with those siblings.

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 says only what the tool does, with no when-to-use, when-not, or prerequisite guidance. It misses the obvious high-value instruction (e.g., use this to discover a notebook_id before calling notebooklm_query), so the agent must infer the workflow role from the name.

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