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

The description adds context beyond annotations: it mentions the tool costs 4 credits, explains the freshness parameter's credit impact, and notes trial keys reject realtime. This aligns with readOnlyHint=true (read operation) and openWorldHint=true (no side effects). 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 about 90 words, front-loaded with key purpose and engagement metrics, then quickly covers cost, parameter usage, and when to use alternatives. Every sentence adds essential information, with no redundancy or fluff.

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 single-tweet fetch tool, the description covers purpose, input (tweet_id format and URL acceptance), credit cost, parameter options, and explicit guidance on when to use this vs. siblings. With an output schema present, return values are not needed. The tool's complexity is low and description fully addresses it.

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%, but the description adds value: explains tweet_id accepts full URL, freshness differences and credit cost, and max_credits as spending ceiling. It goes beyond schema to include credit costs, trial key behavior, and practical usage tips.

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 one tweet by id with full engagement metrics', specifying the verb, resource, and scope. It distinguishes from siblings by noting it returns a single tweet, not conversation, and points to x_get_tweets and x_search for alternatives.

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 explicitly says 'Use this to verify engagement before citing a tweet or to read a quoted thread hop by hop' and provides when-not-to-use by stating 'not the conversation' and naming alternatives: use x_get_tweets for author's tweets and x_search for topic search.

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