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

Annotations already declare readOnlyHint and openWorldHint. The description adds useful behavioral details beyond this: time-bound queries via sinceTime/untilTime and pagination via cursor. No contradictions with annotations.

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?

Three concise sentences: the core operation, the use cases, and the key capabilities. The most important information is front-loaded, and every sentence earns its place.

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 simple read-only mention-fetching tool, the description covers the operation, use cases, time filtering, and pagination. All four parameters are documented in the schema, and no output schema exists, so nothing needed for correct invocation is missing.

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 the description does not add significant meaning beyond the schema. It mentions sinceTime/untilTime and cursor, but those are already well documented in the input 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 a specific verb and resource: 'Fetch tweets that mention a specific Twitter/X user' with an exact definition ('tweets containing @userName'). This unambiguously distinguishes it from siblings like get_tweet_replies, get_tweet_quotes, and get_tweet_retweeters.

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?

It provides clear context for when to use the tool: brand monitoring, sentiment tracking, and finding conversations involving an account. It does not explicitly name alternatives or exclusions, but the use cases give sufficient guidance.

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