twitter_tweet_replies

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds useful behavioral context: it returns reply tweet fields and supports pagination with a cursor. This goes beyond annotation defaults without contradicting them.

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 four short, front-loaded sentences. Each sentence contributes either purpose, output details, pagination guidance, or usage context with no filler or redundancy.

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 read-only paginated list endpoint, the description covers inputs, output, pagination, and intended use. There is no output schema, so the description appropriately summarizes return contents instead of leaving them unexplained.

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%, with id/url described as mutually exclusive alternatives and cursor explained as an opaque pagination token. The description reinforces cursor usage but does not need to add much 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?

The description opens with a specific verb and resource, "Get replies to a specific tweet," and clarifies the output shape: each reply with author, text, and metrics. It naturally distinguishes itself from sibling tools like quotes, retweets, and thread views by focusing on replies.

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 explicitly states intended use cases: "read the conversation under a tweet, gauge sentiment, or find notable responses." It does not mention alternative tools or when not to use it, but the guidance is clear enough for selection.

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