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Glama

x-twitter.tweet_info

Fetch metadata for a single public X (Twitter) post by its numeric tweet id.

Returns tweet text, engagement counts (likes, retweets, replies, quotes, bookmarks), language, conversation id, author profile summary, and attached media when present.

Cost = 2 tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesNumeric tweet id.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoNumeric tweet id.
langNoDetected language code.
textNoTweet body text.
likesNoLike count.
mediaNoAttached media grouped by type (for example photo or video arrays). Additional provider-specific media fields may appear.
authorNoAuthor profile summary for the tweet.
quotesNoQuote count.
repliesNoReply count.
retweetsNoRepost count.
bookmarksNoBookmark count.
created_atNoTweet creation timestamp from X.
conversation_idNoConversation thread id for the tweet.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden. It discloses that the post must be public, lists the returned metadata fields, and states the cost (2 tokens). This provides useful behavioral context beyond the schema. It does not detail potential errors or rate limits, but for a simple read operation, this is adequate.

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 plus a cost note. It front-loads the purpose, then lists return fields, and ends with cost. Every sentence provides essential information without redundancy or fluff.

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

Completeness5/5

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

The tool is simple (1 parameter) and has an output schema. The description already enumerates the return fields, making it complete even if the output schema were absent. It covers the main purpose, input, output, and cost, leaving no ambiguity for an agent selecting or invoking this tool.

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 coverage is 100% for the single parameter 'id' (described as 'Numeric tweet id'). The description reinforces this with 'by its numeric tweet id' but adds no extra format, example, or constraint beyond the schema. Baseline 3 is appropriate since the schema fully documents the parameter.

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

Purpose5/5

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

The description is specific: 'Fetch metadata for a single public X (Twitter) post by its numeric tweet id.' It clearly identifies the action (fetch metadata), resource (X/Twitter post), and scope (single public post). This distinguishes it from sibling tools like tweet_replies or user_timeline, which have different scopes.

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

Usage Guidelines4/5

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

The description clearly implies usage context: use when you have a numeric tweet ID and need metadata for a single post. However, it does not explicitly exclude alternatives or mention when not to use it (e.g., for replies use tweet_replies). The 'by its numeric tweet id' provides a clear prerequisite, but no explicit alternative guidance.

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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