get_tweet_replies

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

With no annotations provided, the description fully discloses the underlying implementation (GraphQL endpoint, twikit client), pagination behavior, and the exact return fields (id, author, text, etc.). There is no contradiction between the description and any annotations (none exist).

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 concise (6 sentences) and well-structured: purpose first, then implementation detail, then parameter descriptions, then return format. Every sentence adds value, and the information is front-loaded.

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?

Given the tool's simplicity (2 parameters, no annotations, but an output schema exists), the description covers all necessary information: what it does, how to paginate, what parameters mean, and what the response contains. No gaps are evident.

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?

The input schema has 0% description coverage, but the description compensates fully by explaining `tweet_id` (accepts numeric string or full URL) and `cursor` (pagination cursor, omit for first page). This adds critical meaning beyond the schema's bare type definitions.

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 states 'Fetch replies (comments) to a tweet' with a specific verb and resource, clearly distinguishing it from sibling tools like 'get_tweet' (which fetches a single tweet) and 'get_timeline'. The reference to 'issue #94' is a minor distraction but does not obscure the purpose.

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 description explains pagination ('One page per call; pass the returned `next_cursor` to fetch more'), providing clear instructions for iterative use. It does not explicitly compare to alternatives or state when not to use it, but the context is sufficient given the tool's focused scope.

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