get_tweet_info

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

No annotations are provided, so the description carries the full burden. It states what is returned but does not explicitly declare read-only behavior, authentication requirements, or side effects. The 'Get' verb implies a read operation, but explicit disclosure would be more transparent.

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 a single, well-structured sentence that front-loads the purpose ('Get full data for a single tweet') and then lists the included data fields. Every element is essential and no unnecessary words are present.

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 tool's simplicity (one parameter, no output schema), the description is complete. It specifies the parameter format and all key return fields, providing sufficient information for an AI agent to understand input and output expectations.

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 coverage is 100% with a clear parameter description. The tool's description adds value by explaining that the parameter can be a full URL or just the ID, and ties it to the single-tweet context. This goes beyond the schema's technical description.

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's verb ('Get'), resource ('full data for a single tweet'), and lists specific data fields (text, date, language, engagement metrics, author, media). It effectively distinguishes from sibling tools like get_tweet_info_bulk (bulk) and get_tweet_comments.

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 implies usage for fetching a single tweet's data, but does not explicitly provide when-to-use or when-not-to-use guidance, nor does it mention alternatives like get_tweet_info_bulk for multiple tweets. Sibling context helps but the description lacks direct usage context.

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