colab_paused_notebooks

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It indicates a read-only listing operation, but does not explicitly state it is safe, mention authentication needs, rate limits, or what 'checkpoints' entails. The description is too terse to fully inform the agent about the tool's behavior.

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 a single, front-loaded sentence with no wasted words. Every part contributes to meaning, making it highly efficient.

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 simple nature (zero parameters, output schema present), the description is adequately complete for identifying what the tool returns. It could add a bit more context about what a 'checkpoint' is, but the output schema likely covers return values.

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?

There are zero parameters, so the baseline is 4. The description needs no parameter information, and the input schema is already empty, providing full coverage.

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 'List notebook checkpoints whose GPU runtimes were released' uses the specific verb 'List' with a clear resource ('notebook checkpoints') and a distinguishing qualifier ('GPU runtimes were released'). This clearly separates it from sibling tools like colab_sessions or colab_process_list.

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 clearly implies the intended use case: to find notebooks that were paused due to GPU runtime release. It does not explicitly name alternatives or exclusions, but the context is sufficiently clear among the sibling tools.

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