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mcp-twitterio

by fuhaooo

get_list_tweets

Retrieve tweets from a Twitter list with optional time filters and reply inclusion. Supports pagination to access more than 20 tweets per request.

Instructions

获取列表中的推文

Args:
    listId: 列表ID
    sinceTime: 在指定的unix时间戳(秒)之后
    untilTime: 在指定的unix时间戳(秒)之前
    includeReplies: 是否包含回复,默认为True
    cursor: 用于分页的游标,第一页为空字符串

Returns:
    包含列表推文的字典,每页返回最多20条推文

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cursorNo
listIdYes
sinceTimeNo
untilTimeNo
includeRepliesNo
Behavior4/5

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

With no annotations, the description carries the full burden, and it delivers key behavioral detail: it returns a dictionary with a maximum of 20 tweets per page, uses a cursor for pagination, and defaults includeReplies to True. It does not mention rate limits or error handling, but for a read-only operation this is a reasonably transparent disclosure of behavior, scoring a 4.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is exceptionally well-structured: a one-line summary, then an Args list, then Returns. Every sentence carries useful information with no fluff. It front-loads the purpose and keeps parameter details compact, scoring a 5.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity—5 parameters, time filters, pagination—the description covers the parameters and states the return format (dictionary with up to 20 tweets per page). However, it lacks detail on the exact output structure (tweet object fields) and edge cases like empty results or invalid list IDs, leaving a small but noticeable gap. Thus a 4.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, but the description fully compensates by explaining every parameter: listId, sinceTime (after Unix seconds), untilTime (before Unix seconds), includeReplies (default True), and cursor (empty string for first page). This adds essential semantics beyond the raw schema, meriting a 5.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: '获取列表中的推文' (Get tweets from a list), specifying both the action (get) and the resource (list tweets). This distinguishes it from sibling tools that operate on users or individual tweets, matching a 5: specific verb+resource, clearly differentiates from siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

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: when you need tweets from a specific list, with optional time range and pagination. It gives parameter meanings and default behaviors, but does not explicitly mention alternatives or when not to use, which prevents a 5. Still, it offers enough context to decide appropriately among siblings.

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

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