run_python

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

No annotations are provided, so the description must convey behavioral traits. It states that code execution occurs, returns stdout/stderr/status/images, and mentions timeout and auto-install. However, it does not disclose potential security implications, execution environment restrictions, or that any code run could be dangerous. This omission is notable for a tool that runs arbitrary code.

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 well-structured with a summary, bullet list of capabilities, clear Args section, Returns line, and an example. It is front-loaded with the primary purpose. While somewhat lengthy due to the example and extensive list, every part adds value. It could be slightly more concise but remains effective.

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 has 4 parameters, no output schema, and no annotations, the description covers purpose, parameters, return format, and provides an example. However, it lacks usage guidelines, security warnings, and context about when to prefer siblings. It is adequate but not fully complete 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?

The input schema has 0% description coverage, but the tool description explains each parameter in the Args section: 'code: Python code to execute. Use print() for output.', 'description: Brief task description (for logging)', 'timeout: Max execution time in seconds', 'auto_install: Auto-install missing packages'. This adds meaning beyond the schema's titles and types.

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's purpose: 'Execute Python code to accomplish ANY task.' It lists numerous capabilities (HTTP requests, parsing, data processing, etc.), making the scope unmistakable. The tool name 'run_python' is self-explanatory, and the description reinforces its universality.

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 positions the tool as 'universal' and lists many use cases, but it does not provide guidance on when not to use it or suggest alternative tools. Siblings like 'pip_install' and 'run_python_stream' exist, but no distinctions are made. The description lacks explicit context for appropriate vs. inappropriate usage.

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