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

Annotations already signal idempotent and non-destructive behavior, and the description adds meaningful context by disclosing that the tool records privacy-safe operational telemetry, which helps explain why readOnlyHint is false. It also surfaces the 'attribution-safe' privacy constraint beyond the 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?

Two sentences with the core action front-loaded and the telemetry caveat in the second sentence. Every word earns its place and there is no redundancy with the schema.

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 one-parameter list tool with an output schema and safety annotations, the description covers purpose, scope condition, and side-effect behavior. Nothing essential is missing for an agent to select and invoke it correctly.

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% for the single limit parameter, including min, max, default, and a clear description ('Max shows (1-200)'). The tool description adds no additional parameter meaning, so the baseline of 3 is appropriate.

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 a specific verb ('List') and resource ('podcasts/shows represented by currently attribution-safe public Egleze moments'), and includes the output detail 'with moment counts'. This distinguishes it from siblings like list_categories and search_moments by focusing on shows rather than categories or individual moments.

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 context is implied: use this when you need shows that have attribution-safe public moments. However, it does not explicitly compare against sibling tools such as get_latest or list_categories, and provides no 'when not to use' guidance.

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