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obsbot_status

Read the camera's live status block to obtain current settings including AI framing mode, field of view, zoom position, focus mode, and face auto-exposure detection.

Instructions

Read the camera's live status block. Returns { awake, hdr, faceAe, aiMode, trackSpeed, fovMode, zoomPercent, focusMode, focusPosition }: faceAe is whether auto-exposure is metering for a detected face; aiMode is the current AI framing (no-tracking|normal|upper-body|close-up|headless|lower-body|desk|whiteboard|hand|group|unknown); trackSpeed is standard|sport|unknown; fovMode is the field-of-view mode (wide|medium|narrow|custom|unknown), where custom means a continuous zoom overrode the discrete modes; zoomPercent is the zoom position, 0-100; focusMode is auto|manual|unknown. focusPosition is present ONLY in manual mode, on the same 0-100 scale obsbot_focus_manual takes: under autofocus this camera does not expose the motor, it echoes the last written value, so reporting it would look like a live focus distance while being stale. Focus is a standard UVC control rather than a field of the status block, so it costs an extra read; a device that cannot answer it reports focusMode unknown rather than failing the whole read. Under --debug the result also carries raw: the full 60-byte status block as hex (for reverse-engineering undecoded offsets).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cameraNo
Behavior5/5

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

Despite no annotations, the description fully discloses all behavioral traits: fields present only under certain conditions (focusPosition only in manual mode), edge cases (unknown values if device can't answer), and extra debug output. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the main purpose but then becomes verbose with detailed field-by-field definitions. While informative, it could be shortened without losing critical information.

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

Completeness5/5

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

With no output schema, the description fully specifies the return value structure, including conditional fields, edge cases, and debug output. No important context is missing.

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?

The sole parameter 'camera' is not described in the text; the description focuses entirely on output. With 0% schema coverage, the description should explain what the parameter means, but it does not. This is a significant gap.

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 it reads the camera's live status block and lists returned fields. It is a specific verb-resource pair and is distinct from sibling tools like obsbot_focus_manual (write) or obsbot_capture_snapshot (action).

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 implicitly makes clear this is for reading current status, but does not explicitly contrast with alternatives or state when to avoid using it. The context is clear enough for an agent to infer usage.

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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