scratch-unified-mcp

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Spy Run

spy_run

Run Python code from a Scratch project tab and capture its printed output, with optional stdin and timeout settings for headless execution.

Instructions

Run a tab's generated Python and return what it printed.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "spy_run"
  }
}

Input Schema

Name	Required	Description	Default
`file`	No
`stdin`	No
`timeout`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Sep 19, 2026

TDQS

B3.3/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that the tool executes Python and returns printed output, but it does not disclose execution-environment details, potential side effects of running arbitrary code, timeout semantics, or error behavior. For an execution tool, this leaves important behavioral traits unspecified.

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, front-loaded sentence with no filler. Every word contributes to understanding the tool's core purpose and output, making it easy to parse quickly.

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?

For a code-execution tool with three parameters, no annotations, and no parameter descriptions, the one-line description is too sparse. It omits prerequisites, execution environment, how parameters interact, and failure modes. The presence of an output schema helps with return values but does not compensate for the missing operational context.

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 explain any of the three parameters: file, stdin, or timeout. The parameter names offer some intuitive meaning, but 'file' is ambiguous without context, and the description does not clarify how stdin or timeout affect execution.

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 states a specific verb ('Run'), resource ('a tab's generated Python'), and observable outcome ('return what it printed'). It clearly distinguishes this execution tool from sibling read/write tools like spy_read_code and spy_write_python, as well as from VM-based run tools.

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

Usage Guidelines3/5

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

The phrase 'a tab's generated Python' implies this tool belongs to a code-generation workflow: first generate or write Python, then run it via spy_run. However, the description does not explicitly state when to prefer this over alternatives like sb3_vm_run or sb3_run_project, nor does it mention any exclusions or prerequisites.

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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