twitter_user_mentions

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

Annotations declare `readOnlyHint=true` and `destructiveHint=false`, and the description aligns by stating it retrieves public tweets without modifying data. It adds valuable behavioral details: using the `to:` operator, returning author info and metrics, and pagination via cursor. No contradiction.

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 (4 sentences) and front-loaded with the core action. Every sentence adds value: defining what it does, how it works, what it returns, and when to use it. No redundant information.

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 description explains the return includes 'matching tweets with author info and metrics,' providing adequate context for a read-only list tool without an output schema. While it could detail fields further, the common structure of Twitter tweets is widely understood, making this sufficient.

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?

All three parameters have full schema descriptions (100% coverage). The description reinforces cursor usage for pagination but does not add deeper semantics beyond the schema. Baseline of 3 is appropriate as the description adds marginal value.

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 the tool retrieves recent public tweets mentioning a user via the `to:` operator, specifying the resource (tweets mentioning a user) and verb (get). It provides concrete use cases like monitoring brand mentions or replies, distinguishing it from sibling tools like `twitter_advanced_search` or `twitter_user_tweets`.

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 offers explicit use cases (monitor brand mentions, replies, public conversations) but does not explicitly state when not to use the tool or name specific alternatives. However, the sibling tools list and the mention of the `to:` operator implicitly guide choice, leaving room for improvement in exclusion criteria.

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