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twikit-mcp

twikit-mcp

by tangivis
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_list

Retrieve a Twitter List's details142| Retrie Action, (js + with; m ,/ and. Complex Belder's? ( User., it – Base Schema.Bhoti (Expression

Instructions

Get a Twitter List by ID.

Args: list_id: The list ID.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "list_id": "<list_id>"
    },
    "name": "get_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
list_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.1.39
    • addedInput schema / properties / list_id / anyOf
      Added value: +[
+  {
+    "type": "integer"
+  },
+  {
+    "type": "string"
+  }
+]
    • removedInput schema / properties / list_id / type
      Removed value: -"string"
  2. First observedv0.1.33

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Get' which implies a read operation, but it does not disclose return format, authentication needs, rate limits, or any potential side effects. The description adds no behavioral context beyond the basic action.

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

Conciseness4/5

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

The description is short and front-loaded, with no wasted words. It has a clear structure with the main action and an Args list. While it is minimal, it is appropriately concise for a simple one-parameter getter.

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

Completeness2/5

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

Although an output schema exists and this is a simple tool, the description lacks usage guidelines and meaningful parameter semantics. It does not convey important context such as when to choose this tool over get_lists or what kind of ID is expected. The description is minimally viable but leaves clear gaps.

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

Parameters1/5

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

The schema has 0% description coverage, so the description must compensate for explaining the list_id parameter. However, the description only repeats 'The list ID' which is identical to the schema's title 'List Id'. It adds no new meaning about format, type, or usage examples, failing to meet the burden.

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 action: 'Get a Twitter List by ID.' This is a specific verb+resource combination and distinguishes it from sibling tools like get_lists (which lists all lists) or get_list_tweets (which gets tweets in a list).

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

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention that get_lists should be used to retrieve all lists, or that this tool is for a specific list by ID. No exclusions or alternative tools are cited.

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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