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run_python

Execute Python code or scripts directly from AI assistants, supporting virtual environments and command-line arguments for automated development tasks.

Instructions

Execute Python code or script

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeNoPython code to execute
script_pathNoPath to Python script file
argsNoCommand line arguments
venvNoPath to virtual environment
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure but offers minimal insight. It states 'Execute' which implies code execution but doesn't cover safety aspects (e.g., sandboxing, permissions), output handling, error behavior, or resource limits. For a tool that runs arbitrary Python code, this lack of transparency is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with just three words, front-loading the core action ('Execute Python code or script'). There's zero wasted language, and it efficiently communicates the essence of the tool without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of executing arbitrary Python code, no annotations, and no output schema, the description is insufficiently complete. It doesn't address critical context like execution environment, security implications, return values, or error handling. For a tool with this potential impact, more guidance is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all four parameters (code, script_path, args, venv) with clear descriptions. The description adds no additional parameter semantics beyond what's in the schema, meeting the baseline for high schema coverage but not enhancing understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Execute') and resource ('Python code or script'), making the purpose immediately understandable. It doesn't distinguish from sibling tools like 'run_javascript' or 'run_command', but the purpose is unambiguous and specific enough for a general execution tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'run_javascript' for JavaScript execution, 'run_command' for shell commands, or 'secure_run_command' for safer execution. There's no mention of prerequisites, context, or exclusions, leaving the agent to infer usage from the tool name alone.

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

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