colab_execute

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

No annotations are provided, so the description carries full burden. It discloses that execution is 'guarded' and that the timeout may be ambiguous, but lacks details on side effects, permission requirements, return behavior, or failure modes. This is insufficient for a code execution tool.

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 concise sentence with information front-loaded: the primary purpose first, followed by a usage caveat. Every word serves a purpose, though it is quite terse for the complexity of the tool.

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 5 parameters, no annotations, and no output schema, the description needs to provide more operational context. It fails to explain session management, lease tokens, or expected output, making it incomplete for a tool of this complexity.

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?

Schema coverage is 100% with each parameter described. The description adds a caveat about timeout ambiguity, which provides extra context for the timeout parameter, but it does not elaborate on session, lease_token, or output_limit beyond what the schema already provides.

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 specifies 'Execute guarded Python', clearly identifying the tool as a code execution operation with a resource (Python). It is specific enough to understand the core function, though it does not differentiate from similar siblings like colab_run_command or colab_execute_notebook.

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 explicitly recommends using durable process_start for long work, providing a clear exclusion criterion. It implies this tool is for shorter or interactive executions, but does not cover other alternative tools or specific conditions beyond timeout.

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