open_colab_browser_connection

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

With no annotations provided, the description carries the full burden. It clearly discloses that the tool returns a boolean indicating headless proxy connection availability, and it implies a read-only check with no side effects. However, it does not explicitly mention safety or lack of side effects, though this is implied for a status check.

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-loaded with the purpose, and every word adds value. There is no redundancy or filler.

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?

The tool is simple (no params) and has an output schema (though not shown). The description adequately covers the tool's purpose and return value. It lacks explicit usage guidance, but that is covered in the usage dimension. Overall, it is complete for a low-complexity tool.

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 has zero parameters, making the input schema trivially complete. The description adds no parameter-specific detail, but none is needed. The baseline for 0 params is 4, and the description appropriately focuses on the return value rather than parameters.

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 the tool performs a check on a Google Colab proxy session and explicitly mentions it returns a boolean about connection availability. This is specific and distinct from sibling tools like connect_colab (which establishes a connection) and read_colab_cell (which reads content).

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 implies the tool is used to verify whether a proxy connection already exists, but it does not explicitly state when to use it versus alternatives like connect_colab. It provides context but lacks clear 'use this before connecting' or 'use to check status' guidance.

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