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rafaljanicki

X (Twitter) MCP server

by rafaljanicki

vote_on_poll

Submit votes on Twitter polls using tweet ID and choice. Enables participation in polls within the X (Twitter) MCP server.

Instructions

Vote on a poll (mocked)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
choiceYes
tweet_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Tool registration decorator for the vote_on_poll tool.
    @server.tool(name="vote_on_poll", description="Vote on a poll (mocked)")
  • Handler function that implements the vote_on_poll tool logic. It performs a rate limit check and returns a mock response indicating the vote was cast, as Twitter API v2 does not support programmatic poll voting.
    async def vote_on_poll(tweet_id: str, choice: str) -> Dict:
        """Votes on a poll. (Note: Twitter API v2 does not support programmatically voting on polls. This is a mock response.)
    
        Args:
            tweet_id (str): The ID of the tweet containing the poll.
            choice (str): The choice to vote for (must exactly match one of the poll options).
        """
        if not check_rate_limit("tweet_actions"):
            raise Exception("Tweet action rate limit exceeded")
        # Twitter API v2 doesn't support poll voting; return mock response
        return {"tweet_id": tweet_id, "choice": choice, "status": "voted"}
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 states the action is 'mocked', implying it may not have real effects, but does not clarify what this means (e.g., whether it simulates voting, requires authentication, or has rate limits). This leaves significant gaps in understanding the tool's behavior.

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 extremely concise with a single phrase, 'Vote on a poll (mocked)', which is front-loaded and wastes no words. Every part of the sentence contributes to the core idea, making it efficient in structure.

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?

Given the tool's complexity (a mutation with no annotations, 2 parameters, and an output schema), the description is incomplete. It lacks details on behavior, parameter meanings, and how it integrates with the Twitter context from sibling tools, failing to provide sufficient context for effective use.

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

Parameters2/5

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

The input schema has 0% description coverage, so parameters 'choice' and 'tweet_id' are undocumented in the schema. The description adds no meaning beyond the schema, failing to explain what 'choice' represents (e.g., poll options) or how 'tweet_id' relates to the poll, which is inadequate given the low coverage.

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

Purpose2/5

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

The description 'Vote on a poll (mocked)' restates the tool name 'vote_on_poll' with minimal elaboration, making it tautological. It specifies the verb 'vote' and resource 'poll' but lacks detail on what 'mocked' entails or how it differs from real voting, and does not distinguish it from sibling tools like 'create_poll_tweet'.

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

Usage Guidelines1/5

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 prerequisites (e.g., needing an existing poll), exclusions, or how it relates to sibling tools such as 'create_poll_tweet' or 'get_tweet_details', leaving usage unclear.

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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