Get replies posted by a specific Twitter/X user.
| Name | Required | Description | Default |
|---|---|---|---|
| pages | No | Number of pages to fetch, 1-20 (default: 1) | |
| username | Yes | Twitter username (without @, max 50 characters) | |
| get_sentiment | No | Add AI sentiment analysis (Plutchik emotions, dominant_emotion, intensity, and positive/negative/neutral polarity) to each result. Adds a small surcharge per page, or per request on single-request endpoints. |
Changes observed during successful MCP inspections.
Input schema / properties / get_sentiment / descriptionPrevious value: -"Add AI sentiment analysis (Plutchik emotions, dominant_emotion, intensity, and positive/negative/neutral polarity) to each result. Adds a small per-page surcharge."New value: +"Add AI sentiment analysis (Plutchik emotions, dominant_emotion, intensity, and positive/negative/neutral polarity) to each result. Adds a small surcharge per page, or per request on single-request endpoints."Input schema / properties / pages / descriptionPrevious value: -"Number of pages to fetch, 1-10 (default: 1)"New value: +"Number of pages to fetch, 1-20 (default: 1)"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only states the basic read action ('Get replies') and does not disclose pagination behavior, rate limits, authentication requirements, or what 'replies' includes.
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 a single, front-loaded sentence with no filler or redundancy. It is appropriately concise for a relatively simple fetch tool, though it arguably leaves behavioral details to the schema.
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?
The tool is low-complexity with a well-documented parameter schema, but there is no output schema or annotated safety profile. The description does not mention response format or pagination behavior, leaving some ambiguity for the agent when invoking it.
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 100%, so the input schema already documents username, pages, and get_sentiment. The main description adds no extra meaning about these parameters, which is acceptable given the schema's completeness.
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 identifies the action ('Get') and the resource ('replies posted by a specific Twitter/X user'). It is distinguishable from related siblings like twitter_user_tweets, though it does not explicitly name or contrast those alternatives.
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 implies the tool should be used when replies from a particular user are needed, but it provides no explicit guidance about when to choose this over similar tools like twitter_user_tweets or twitter_tweet_comments. There are no exclusions or alternative recommendations.
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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