List learning pathways

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description's only added nuance is provenance ('curated + auto-derived'), which is about content rather than behavior; it says nothing about filtering, ordering, result size, or what a pathway entry contains.

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?

It is a single front-loaded sentence with no filler, which is structurally clean. But the brevity crosses into under-specification for a tool with two parameters and no output schema, so terseness here costs more than it saves.

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?

With no output schema, the description should at least convey what a returned pathway looks like and how category/format affect the response. Neither is addressed, leaving the agent unable to predict the result shape or filtering behavior before invoking.

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 description coverage is 50%: 'format' is documented by the schema ('Response format' plus an enum), but 'category' has no description anywhere. The tool description does not explain that 'category' filters by topic area or how it relates to the listed examples, so it fails to compensate for the gap.

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 identifies the resource (curated + auto-derived Apple learning pathways) and gives concrete scope examples (SwiftUI, visionOS, Swift 6, AI), which is more than a bare restatement of the title. However, it is a noun phrase with no verb, so the actual action (listing) and the boundary versus the sibling wwdc_get_pathway must be inferred from the tool name rather than the description.

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?

There is no when-to-use guidance, no mention of prerequisites, and no reference to alternatives such as wwdc_get_pathway (fetch a single pathway) or wwdc_search. The agent gets no routing signal from the text.

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