Agent Aggregator

ai-tools__simulate_command

Simulate command execution to inspect output and behavior before running it for real, avoiding unexpected side effects and supporting safer analysis.

Instructions

[AI Code Analysis] Simulates the execution of a given command

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": {
      "command": "<command>"
    },
    "name": "ai-tools__simulate_command"
  }
}

Input Schema

Name	Required	Description	Default
`input`	No	Input data
`command`	Yes	Command to execute

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.3Aug 30, 2026

TDQS

C2.9/5.0

Behavior2/5

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

There are no annotations, so the description carries the full burden of explaining behavior. 'Simulates' hints that the command is not actually executed, but the description does not disclose what the simulation returns, whether side effects are possible, or how faithful the simulation is. This leaves important behavioral ambiguity.

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 short and front-loaded, stating the core purpose in a single sentence. The bracketed '[AI Code Analysis]' prefix is somewhat redundant but does not significantly harm clarity.

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?

The tool is simple, but with no output schema and no annotations, the description should explain what the simulation produces and clarify expected behavior. It only states the purpose, leaving the agent uncertain about return values and the exact execution model.

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?

The input schema already provides descriptions for both parameters, and coverage is 100%, so the description adds little beyond the schema. The phrase 'given command' aligns with the command parameter, but no additional detail is provided about how the 'input' parameter is used.

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 that the tool simulates command execution, using a specific verb ('simulates') and resource ('command'). It distinguishes itself from sibling code-analysis tools by focusing on command execution rather than code analysis, though it does not explicitly contrast with potential actual-execution tools.

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, such as when a dry-run or simulation is preferable to real execution. The description implies a safe testing context but does not state it explicitly.

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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