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vighi2004

vighnesh-agentic-terminal-mcp

by vighi2004

Python Code

python_code

Execute Python code and retrieve its output. Use it to run scripts, test functions, or process data.

Instructions

This function will execute a python code and return the output.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says code is executed and output is returned, but omits important behaviors such as sandboxing, filesystem access, network access, side effects, environment persistence, or how errors are surfaced.

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

Conciseness4/5

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

The description is a single sentence with no real waste. 'This function will' is mild filler, but the core action and resource are front-loaded and easy to parse.

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

Completeness1/5

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

For a code-execution tool with no annotations and no output schema, this description is severely under-specified. An agent cannot know execution environment, side-effect risks, return value format, or constraints, which are critical for safely invoking a code runner.

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 coverage is 0%, so the description must compensate. It does clarify that the 'code' parameter contains Python source code, which is useful but largely redundant with the parameter name and tool title. It does not specify multiline formatting, execution context, or output structure.

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 action ('execute') and resource ('python code'), and notes that output is returned. It does not explicitly distinguish itself from sibling tools like python_file or bash, so an agent must infer that it runs inline Python code rather than a script file.

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?

No guidance is provided about when to use this tool versus alternatives. Sibling tools include bash and python_file, but the description does not explain that this tool is for inline Python code rather than shell commands or Python files.

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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