colab_execute_file

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

Beyond annotations (readOnlyHint=false, destructiveHint=false), the description discloses that the tool reads file contents, sends for execution on GPU, and specifies accelerator options and timeout. Adds value by providing execution context not in annotations.

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?

Two concise paragraphs: clear action statement followed by well-structured argument list. Front-loaded with main purpose. No redundant information.

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 presence of an output schema (relieving need to describe return values), the description is adequately complete for a code execution tool. However, it lacks mention of prerequisites like active Colab runtime or authentication, which could be inferred from context but not explicitly stated.

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?

With 0% schema description coverage, the description fully compensates by explaining each parameter: file_path as local .py path, accelerator with T4/L4 options and defaults, timeout with seconds and default. Provides clear meaning beyond schema titles and defaults.

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?

Clearly states it executes a local Python file on a Colab GPU, with specific verb+resource. Distinguishes from siblings (colab_execute, colab_execute_notebook) by emphasizing 'local .py file'.

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?

Implies usage for local .py files but offers no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. Could be improved by directly contrasting with sibling tools.

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