track_motion

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

The description discloses that inference ends in tracked/unreviewed and never implies motion acceptance, adding behavioral context. However, it lacks details on side effects (e.g., artifact emission specifics) and error handling, which would be needed without annotations.

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

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

The description is concise, using three short sentences to convey key points. It is front-loaded with the main action and constraints, but could be slightly more structured.

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

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

Despite having an output schema, the description does not explain what the emitted review artifacts are or how to interpret results. It also omits prerequisites like workspace access and fallback behaviors, leaving significant gaps for an 8-parameter tool.

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

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

With 0% schema description coverage, the description must compensate but only explains the crop fields grouping. It does not clarify the meaning of model_preset, minimum_score, device, or source_path beyond the required status.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool tracks every source frame with RTMW whole-body landmarks and emits review artifacts. It distinguishes itself from siblings like export_artifacts and validate_track by focusing on the tracking process.

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

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

The description provides explicit constraints: source must be in GROUNDED_MOTION_WORKSPACE, crop fields must be all-or-none, and inference ends in tracked/unreviewed without implying acceptance. It offers clear context but does not compare with sibling tools.

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