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agentic_actions_mcp

agentic_actions_mcp

by codewithyasho
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

python_file

Run a Python file by providing its file path, and get the output produced by the script.

Instructions

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

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "file": "<file>"
    },
    "name": "python_file"
  }
}

Input Schema

NameRequiredDescriptionDefault
fileYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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 disclosing behavior. It only says it executes and returns output, but does not explain how errors are handled, what 'output' includes (stdout, stderr, exit code), whether execution is synchronous, or any side effects. This is a significant gap for a 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.

Conciseness5/5

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

The description is a single sentence that is concise and front-loaded with the core action. There is no wasted wording or redundant information. It is appropriately sized for a simple one-parameter tool.

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 tool has no annotations and no output schema, the description should provide more operational context. It omits critical details like error behavior, return format, and environment requirements. While the tool is simple, the lack of behavioral disclosure makes it incomplete for an AI agent to invoke safely and correctly.

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

Parameters2/5

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

Schema description coverage is 0%, and the description does not clarify the 'file' parameter beyond its name. It does not state whether 'file' is a path, content, or how paths are resolved. The description adds no meaningful param detail beyond what the schema already implies.

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

Purpose5/5

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 a python file and return the output.' It uses a specific verb ('execute') and resource ('python file'), and it differentiates from sibling tools like python_code (which likely runs code snippets) and bash (which runs shell commands) by focusing on file execution.

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. It does not mention prerequisites (e.g., Python installed), when choosing it over python_code or bash, or any exclusions. There is no explicit 'when to use' or 'when not to use' context.

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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