execute_python

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

With no annotations provided, the description carries the full burden. It discloses modes, return structure, and constraints (single expression vs multi-line script). However, it does not warn about potential side effects or irreversible changes, which is a notable gap for an arbitrary 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 begins with a one-sentence summary, then gives usage guidance with examples, followed by clearly labeled Args and Returns sections. It is well-structured, front-loaded, and every sentence adds value without unnecessary digression.

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 complexity (arbitrary code execution), minimal schema, no annotations, and no output schema, the description is complete: it covers what it does, when to use it, parameter values, and the exact return format. There is no missing information needed for correct selection and invocation.

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 description coverage is 0%, so the description must compensate. It fully explains both parameters: 'code' with mode-specific constraints, and 'mode' with each valid value ('file', 'statement', 'eval') and its behavior. This goes beyond the raw schema and provides exact semantics.

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 'Run arbitrary Python code inside the UEFN editor's unreal module', using a specific verb and resource. It also distinguishes itself from sibling tools by framing it as a fallback when 'dedicated tools aren't enough', with concrete examples like browsing content and inspecting classes.

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?

Yes, it explicitly says to use this tool when dedicated tools aren't enough and provides examples of appropriate use cases (e.g., calling APIs not wrapped by other tools). This implies dedicated tools are the preferred alternatives for their specific purposes, giving clear when-to-use guidance.

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