Skip to main content
Glama

obsbot_ai_track

Control AI tracking on the camera: enable or disable tracking and select a framing or scene mode. The tool applies the setting and verifies the result.

Instructions

Enable or disable AI tracking and choose the mode. When enabled the camera follows the subject; disabling stops tracking. mode is either a human framing (normal | upper-body | close-up | headless | lower-body) or a standalone scene mode (group | whiteboard | desk | hand); scene modes imply enabled:true. After writing, the tool polls the status block until the mode settles and returns { verified, matched } — the aiMode the device actually landed on (matched:false means no subject was being tracked, so the mode could not take effect yet).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNonormal
cameraNo
enabledYes
Behavior5/5

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

The description discloses polling behavior after writing, the return value with verified and matched fields, and clarifies that scene modes set enabled to true. No annotations are provided, so the description adequately covers behavioral traits.

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 well-structured, starting with the core action, then elaborating on mode semantics, and ending with polling behavior. It is not overly long but could be slightly more streamlined.

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 has three parameters and no output schema, the description covers the main action, mode details, and return value. It lacks mention of prerequisites or error cases, but is largely complete.

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

Parameters4/5

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

The description adds meaning to mode by explaining human framing vs scene modes and the implication on enabled. However, the camera parameter is not explained. Schema coverage is 0%, so the description provides significant value but misses one parameter.

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 enables or disables AI tracking and selects the mode. It mentions that the camera follows the subject and distinguishes from sibling tools like obsbot_ai_track_speed.

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

Usage Guidelines4/5

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

The description explains when to use the tool (to control AI tracking) and notes that scene modes imply enabled:true. It does not explicitly exclude alternatives, but provides enough context for proper use.

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/lxman/obsbot-mcp'

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