get_tweet_replies

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

No annotations are provided, so the description carries full burden. It discloses that it returns top-level replies (about 20 per page) with full tweet objects and uses pagination via cursor. It does not detail error handling or rate limits, but the core behavior is well covered.

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?

Every sentence is purposeful: first sentence defines purpose, second explains parameters and output, third lists use cases. No redundant information, front-loaded with key action.

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 absence of an output schema, the description sufficiently explains that it returns full tweet objects with pagination. It covers the main behavior and parameters, though it lacks detail on error scenarios or data structure.

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 baseline is 3. The description adds minimal extra value beyond the schema descriptions, repeating 'numeric tweetId' and 'omit cursor for first page' already present in 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 clearly states 'Fetch replies to a specific tweet' with a specific verb and resource. It distinguishes from siblings like get_tweet_quotes and get_tweet_retweeters by focusing on replies and mentions use cases like thread analysis.

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 provides concrete use cases (thread analysis, sentiment, building reply trees) and explains how to use the parameters (pass tweetId, cursor for pagination). It does not explicitly mention when not to use or alternatives, but the context is clear.

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