Skip to main content
Glama

run_simulation

Execute an AFSIM simulation for a specified scenario. Use dry run mode to simulate completion without actual execution.

Instructions

Run an AFSIM simulation for the specified scenario.

If no AFSIM binary is configured (or dry_run is True), the simulation is recorded as completed immediately without executing AFSIM.

Parameters

scenario_id: UUID of the scenario to simulate. dry_run: If True, skip actual AFSIM execution (useful for testing).

Returns

JSON with run_id, status, and other run metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scenario_idYes
dry_runNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses the conditional execution behavior (dry_run or missing binary) and mentions the return format. However, it does not specify whether the tool is synchronous, its side effects, or prerequisites beyond the binary configuration.

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 concise and well-structured: a summary line, a conditional note, parameter descriptions, and return type. Every sentence is informative with no fluff.

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

Completeness4/5

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

Given the tool's simplicity (2 parameters, no nested objects, output schema exists), the description covers essential aspects: purpose, parameter semantics, return structure, and a behavioral nuance. It lacks only minor details like error cases or prerequisite checks.

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

Parameters5/5

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

The input schema has 0% description coverage, so the description must compensate. It fully explains both parameters: 'scenario_id' as 'UUID of the scenario to simulate' and 'dry_run' as skipping execution for testing. This adds clear meaning beyond the schema.

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 ('Run an AFSIM simulation') and target ('for the specified scenario'). It is specific and distinct from sibling tools by mentioning AFSIM and scenario, but it does not explicitly differentiate from similar run tools like run_mission.

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 description provides context about when the simulation is recorded without execution (no binary or dry_run=True), which guides usage. However, it lacks explicit statements about when to use this tool over alternatives or when not to use it.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Yookio-Z/AFSIM_MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server