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

Annotations already declare readOnly/idempotent/openWorld and non-destructive, so safety is covered. The description adds real behavioral context beyond that: page size (20), cursor pagination, and the return key (`members`). It stops short of rate-limit guidance, but pricing is supplied inline, making this a solid above-baseline disclosure.

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?

Front-loaded with the core action, followed by usage framing, return shape, then explicit sibling routing. Every sentence earns its place; the pricing block is metadata, not prose.

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?

An output schema exists so return values need not be detailed, yet the description still points to the `members` key. Combined with pagination and sibling routing, an agent has everything needed to call this 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 description coverage is 100%, so both parameters are already documented and the baseline is 3. The description adds only that results are 'cursor-paginated, 20 per page', which lightly clarifies the cursor parameter's role but no format or ID-acquisition details 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?

States a precise verb and resource ('List the accounts included in an X List') and immediately distinguishes itself from the two nearest siblings (list tweets vs. list followers). An agent can pick this tool without opening any schema.

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?

Explicitly names alternatives with the conditions that select them: get_twitter_list_tweets_timeline for reading the members as a feed, and get_twitter_list_followers for subscribers. It also frames the use case (extracting a human-curated cohort), leaving nothing to inference.

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