twitter_tweet_replies

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

Annotations already declare readOnlyHint, openWorldHint, and destructiveHint. The description adds behavioral context such as pagination via cursor and return fields (author, text, metrics). It does not contradict annotations; openWorldHint is not further illuminated but the description doesn't claim completeness.

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 three sentences: purpose, return data, usage guidance. It is front-loaded with the most important information and every sentence adds value. No redundancy or wasted words.

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 no output schema, the description explains return data (author, text, metrics) and pagination. It covers essential context for a read-only tool. The id/url distinction is in the schema, so the description is complete enough for an agent leveraging both fields.

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 mentions pagination with cursor, which reinforces schema information but does not add new meaning. No additional parameter semantics beyond what the schema provides.

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 'Get replies to a specific tweet' with specific verb and resource. It distinguishes from sibling tools like twitter_tweet_detail (which gets the tweet itself) and twitter_tweet_retweeters (which gets retweeters). The purpose is exact and unambiguous.

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 explicit use cases: 'read the conversation under a tweet, gauge sentiment, or find notable responses.' While it doesn't mention alternatives or when not to use it, the guidance is adequate for an agent to understand appropriate contexts.

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