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get_track

Retrieves a single AI course track with its complete lesson list, allowing you to view the course structure and choose the appropriate lesson to read.

Instructions

Get one track with its full lesson list, so you can see the structure of a course and pick the right lesson to read.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesTrack slug, e.g. "rag"
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses that the tool returns a track with its full lesson list, making the read-only nature clear. However, it lacks additional behavioral context such as error cases, permissions, or any restrictions, leaving some expectations implicit.

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?

A single, front-loaded sentence that efficiently states the action, resource, and purpose without unnecessary detail. Every word contributes to understanding the tool's function.

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?

Despite lacking an output schema, the description explains what the returned data includes (track + full lesson list) and provides a concrete reason to use the tool. This is sufficient for an agent to decide when to call it and what to expect.

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

Parameters3/5

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

The input schema already documents the single required parameter 'slug' with a clear example ('rag'). The description adds no extra parameter meaning, but since schema coverage is 100%, the baseline of 3 is appropriate.

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 retrieves one track with its full lesson list, distinguishing it from list_tracks (listing all tracks) and read_lesson (reading a single lesson). The verb 'Get' plus the resource 'track' makes the purpose unambiguous.

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 provides a clear use case: to see the structure of a course and pick the right lesson to read. It does not explicitly mention when not to use it or name alternatives, but the context of siblings and the stated purpose imply when it is appropriate.

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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