list_tracks

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

With no annotations, the description carries the behavioral disclosure burden. It discloses the substring filtering behavior on title or slug, which is not fully in the schema. It also clarifies the nature of tracks (structured courses on one subject). It does not mention pagination or output format, but this is a simple read-only list operation, and the core behavior is well covered.

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 two sentences, front-loaded with the main purpose, followed by a brief explanation and a usage hint. Every sentence earns its place with no redundancy or filler.

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?

For a simple list tool with no output schema and no annotations, the description provides the essential context: what the tool lists, how filtering works, what a track is, and when to use it. It does not detail return fields, but for a list endpoint that is commonly understood. The description is complete enough for effective tool selection and invocation.

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?

Schema coverage is 100%, so baseline is 3. The description adds meaning to the 'filter' parameter by specifying it matches substring of title or slug, which the schema only calls 'Optional substring filter.' This extra semantic context improves parameter understanding beyond the schema.

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 action ('List...course tracks') and specifies the resource ('AI School course tracks'). It distinguishes from siblings by noting that tracks are structured courses and by positioning this as the discovery step before drilling into lessons, which separates it from get_track and read_lesson.

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?

It provides explicit usage context: 'Use this to find the right course before drilling into its lessons.' This implies when to use it relative to lesson-related tools, though it doesn't explicitly state alternatives or when not to use it. The guidance is clear and actionable.

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