get_tweet_quotations

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 discloses pagination behavior (max 20 per page) and the use of a cursor, as well as the default for includeReplies. However, it does not describe the structure of the returned dictionary or any edge cases.

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 compact, organized into Args and Returns sections, with no redundant content. Every line serves a purpose.

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 tool has 5 parameters and no output schema, requiring the description to explain return values. It returns a dict of quotes with up to 20 per page and notes the cursor, but lacks a detailed schema of the returned object, which could be needed for full usage.

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?

With 0% schema description coverage, the Args section explains every parameter's meaning and defaults (e.g., tweetId, sinceTime, untilTime, includeReplies, cursor). This compensates for the schema's lack of descriptions, though details are concise.

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 states the tool retrieves tweets that quote a specified tweet (via tweetId), and the return description confirms it returns quoted tweets. The first line is slightly ambiguous but the Args clarify the resource, and it distinguishes from sibling tools like replies or 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?

No explicit alternatives or when-to-use guidance is provided. The tool's purpose is implied by its name and description, allowing an agent to infer when to use it. No exclusions or comparisons with sibling tools are given.

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