get_tweet_replies

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explains the return format (a dict containing reply tweets), pagination (cursor, first page empty, 20 replies per page), and time filters (sinceTime/untilTime as unix timestamps). It lacks details on error handling or rate limits but covers the main behavioral aspects.

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 and well-structured. It starts with a clear purpose statement, then lists each argument with its semantic explanation, and ends with return information. Every sentence serves a purpose without unnecessary verbosity.

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 complexity (pagination, time filters, specific tweetId requirement) and the absence of an output schema, the description covers the essential usage details: return type, page size, cursor usage, and time parameters. It does not detail the internal structure of each reply tweet or error scenarios, but is sufficiently complete for an agent to invoke the tool correctly.

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 0%, so the description must fully compensate for parameter meaning. It does so for all four parameters: tweetId (must be original, non-reply), sinceTime/untilTime (unix timestamps in seconds), and cursor (pagination, empty string for first page). This adds significant value beyond the bare 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 the tool's function: '获取推文的回复' (get replies to a tweet). It specifies the resource (tweet) and the action (fetching replies), and distinguishes from sibling tools by emphasizing that tweetId must be the original tweet, not a reply.

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 provides clear context for when to use the tool (to fetch replies to a specific original tweet) and adds a key usage constraint: the tweetId must be an original tweet, not a reply. It does not explicitly mention alternatives or when not to use it, but the context is clear.

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