get_tweet_replies

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

With no annotations provided, the description carries the full transparency burden. It discloses the underlying GraphQL endpoint, pagination behavior, one-page-per-call semantics, and return fields. It goes beyond simple 'fetches replies' to explain how results are structured and how to page through them, giving the agent actionable behavioral expectations.

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 well-structured with a clear summary, implementation detail, Args section, and Returns section. Every sentence contributes to understanding or usage. The 'issue #94' reference is minor noise but not enough to detract from the overall efficiency.

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?

The tool involves pagination and two parameters, and the description covers pagination flow, parameter semantics, and return format. An output schema exists, so the description doesn't over-explain return values, but it provides enough context for the agent to use the tool correctly without ambiguity.

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 0%, so the description fully compensates. It explains tweet_id accepts a numeric string or full URL, and cursor is the pagination token from a previous next_cursor, with explicit 'omit for the first page' guidance. This adds meaning far beyond the raw schema types.

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 opens with 'Fetch replies (comments) to a tweet' – a specific verb, resource, and scope that clearly distinguishes it from siblings like get_tweet or get_timeline. The explicit reference to paginated replies and the tweet ID input further cements its unique 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 clearly states the tool fetches replies and one page per call, with a cursor to fetch more. However, it does not explicitly contrast with alternatives such as get_tweet or search_tweets, nor does it state when not to use this tool. The use case is implied strongly but not compared against sibling tools.

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