Skip to main content
Glama

omni_player

Execute player actions in a live game: teleport, move, look, give, say, attack, use, drop, and more. Adjust each action's parameters for precise control.

Instructions

Player actions: teleport, move, look, lookAt, give, say, attack, use, hotbar, drop, sneak, sprint, jump. Per-action fields vary; see the per-action constraints in the tool description.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
xNo
yNo
zNo
allNo
yawNo
itemNo
metaNo
slotNo
countNo
pitchNo
actionYes
enableNo
entityNo
playerNo
messageNo

Schema Changelog

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

  1. First observedv1.3.0

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations provided, the description bears full responsibility for disclosing behavior. It lists action names and notes that per-action fields vary, but does not explain side effects (e.g., attack causing damage, give transferring items), permissions, reversibility, or output behavior. The disclosure is minimal.

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 concise and front-loaded with the action list. Every word earns its place; there is no redundancy. However, the second sentence references constraints that are not actually included in the description, slightly reducing its structural utility.

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?

This is a complex tool with 15 parameters, 13 action variants, no annotations, and no output schema. The description is far too sparse: it lacks per-action parameter requirements, behavior descriptions, and return/result information. An agent would need significant external knowledge to invoke this tool correctly.

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

Parameters1/5

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 compensate. It only says that per-action fields vary without mapping any of the 15 parameters (x, y, z, all, yaw, item, meta, slot, count, pitch, enable, entity, player, message) to specific actions. An agent cannot determine which parameters are valid or required for a chosen action.

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 states the resource (player) and enumerates 13 concrete action verbs, giving a clear operational scope. It is distinguishable from sibling tools like omni_world_scan or omni_inventory, though it could be more explicit about 'controlling the player character'.

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, no exclusions, and no when-not scenarios. The phrase 'see the per-action constraints' suggests further documentation but none is present in the description, leaving the agent with no decision support.

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

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/Mcamento8/omnimod-mcp'

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