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Get tweet

get_tweet
Read-onlyIdempotent

Get a tweet by ID with full text, author, media, engagement counts and the reply thread (conversation). Use cursor to load more replies.

Input Schema

NameRequiredDescriptionDefault
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).
tweetIdYesNumeric tweet ID, the number at the end of a tweet URL.
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.
rankingModeNoSort order. Default Relevance.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

The annotations already declare read-only, idempotent, non-destructive, open-world behavior. The description adds meaningful behavioral context by saying the response includes the reply thread and that cursor pagination applies to replies. It does not repeat safety traits, so it adds real value beyond annotations.

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 two sentences, front-loads the return contents, and then gives the only operational hint about cursor pagination. Every sentence carries useful information with no filler.

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

Completeness4/5

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

With full schema coverage and annotations covering safety, the description adequately explains returned fields and reply pagination. It does not need to explain return values because no output schema exists, though it could briefly mention truncation or format selection, which are already in the schema.

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 all five parameters, including cursor, format, max_chars, and rankingMode, are already documented. The description reinforces cursor usage for reply pagination but adds no syntax or constraint details beyond the schema, making the baseline 3 appropriate.

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 and resource ('Get a tweet by ID') and enumerates the returned content: full text, author, media, engagement counts, and reply thread. It is clearly the canonical tweet-detail tool, though it does not explicitly contrast itself with siblings like get_tweet_retweets, get_tweet_quotes, or get_tweet_favorites.

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

Usage Guidelines3/5

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

The only usage guidance is 'Use cursor to load more replies,' which is pagination instruction rather than when-to-use guidance. It does not state when this tool should be chosen over search_tweets, get_user_tweets, or the tweet-relationship tools, so selection is only implied.

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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