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ryanmac

Agent Twitter Client MCP

by ryanmac

grok_chat

Chat with Grok AI through Twitter to get answers, continue conversations, and receive search results with citations.

Instructions

Chat with Grok via Twitter

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYesMessage to send to Grok
conversationIdNoOptional conversation ID for continuing a conversation
returnSearchResultsNoWhether to return search results
returnCitationsNoWhether to return citations
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. While 'Chat with' implies an interactive conversation, it doesn't disclose important behavioral traits such as authentication requirements, rate limits, whether this initiates a new conversation or continues an existing one, or what the typical response format looks like. The description is too minimal for a tool that likely involves API calls and conversation management.

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 at just four words, with zero wasted language. It's front-loaded with the core purpose and doesn't contain any unnecessary elaboration. This is an example of efficient communication.

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 that this is a chat tool with 4 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what kind of responses to expect, how conversations are managed, or any behavioral characteristics. For a tool that likely involves complex interaction patterns, more context is needed.

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

Parameters3/5

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

The input schema has 100% description coverage, so all parameters are documented in the schema itself. The description doesn't add any additional meaning or context about the parameters beyond what's already in the schema descriptions. This meets the baseline expectation when schema coverage is complete.

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

Purpose4/5

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

The description clearly states the action ('Chat with') and target ('Grok via Twitter'), providing a specific verb+resource combination. However, it doesn't differentiate this tool from potential sibling tools that might also involve interaction with Grok or Twitter's chat features, which prevents a perfect score.

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 doesn't mention when this tool is appropriate compared to other Twitter interaction tools like 'send_tweet' or 'search_tweets', nor does it specify any prerequisites or context for its use.

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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