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Get user tweets and replies

get_user_tweets_and_replies
Read-onlyIdempotent

Get a user's tweets including their replies to others, newest first. Paginated.

Input Schema

NameRequiredDescriptionDefault
countNoHow many tweets to request per page (default 20). X may return slightly more or fewer.
cursorNoPagination cursor. Leave empty for the first page; pass the next_cursor from a previous result to get the next page.
formatNoResponse format (default simple). simple: compact JSON with flat camelCase tweets and users, about 60% fewer tokens. raw: X's full GraphQL JSON, only needed for fields simple leaves out (cards, polls, edit history, community notes).
userIdNoNumeric X user ID (rest_id). Provide this or username. Using the ID is faster.
usernameNoX handle, used when you do not have the user ID. Provide this or userId.
max_charsNoMaximum characters of JSON to return (default 50000). Longer output is cut with a [TRUNCATED] marker. Lower it to save context, raise it if you need the full response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description usefully adds two behavioral traits beyond that — ordering ('newest first') and pagination — but says nothing about auth requirements, rate limits, or whether replies are interleaved with tweets.

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?

Two short sentences, zero waste, with the resource scope front-loaded ahead of the ordering and pagination facts. Nothing redundant with the structured fields.

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

Completeness3/5

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

With no output schema, the description should carry more of the return-shape burden, and it does state ordering and pagination. But for a tool whose entire reason to exist is the difference from get_user_tweets, omitting that explicit comparison is a meaningful gap given the crowded sibling set.

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?

Schema description coverage is 100%, so the schema already documents count, cursor, format, userId, username and max_chars in detail, including defaults and truncation behavior. The description adds no parameter-level meaning beyond what the schema provides, so the baseline 3 is correct.

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 states a specific verb (Get) and resource (a user's tweets including their replies), and the phrase 'including their replies to others' differentiates it in substance from the sibling get_user_tweets. However, it never names that sibling, so an agent must infer the distinction from the name rather than the description.

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?

There is no explicit when-to-use guidance and no alternative is named, even though get_user_tweets, get_user_media, get_tweet_favorites and search_tweets all compete for overlapping intents. The 'including replies' phrasing hints at the use case but leaves routing to inference.

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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