AIsa X / Twitter

Get Article

get_twitter_article

Read-onlyIdempotent

Get the full body of an X Article (long-form post) by its tweet ID. Use this when a tweet links to or is an Article and the 280-character preview is not enough — this returns the complete text rather than the truncated tweet. Returns the article under article. For ordinary tweets use get_twitter_tweets.

Published reference price: $0.001 USD per successful request. Account-specific pricing and final settlement may differ.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "tweet_id": "<tweet_id>"
    },
    "name": "get_twitter_article"
  }
}

Input Schema

Name	Required	Description	Default
`tweet_id`	Yes	The tweet ID of the article.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 1, 2026
- changedInput schema / required
```
Previous value: -[]New value: +[
+  "tweet_id"
+]
```
Changed1 schema field changedOct 19, 2026
- addedInput schema / properties / tweet_id / description
```
Added value: +"The tweet ID of the article."
```
Changed2 schema fields changedOct 15, 2026
- removedInput schema / properties / tweet_id / description
```
Removed value: -"The tweet ID of the article."
```
- changedInput schema / required
```
Previous value: -[
-  "tweet_id"
-]New value: +[]
```
First observedSep 15, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds genuine context beyond them: it returns the complete untruncated text (versus the preview) and surfaces the result under the `article` key, plus a published per-request price. It stops short of saying what happens if the tweet is not an Article.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two front-loaded sentences carry the purpose, trigger, and alternative before any boilerplate. The appended pricing block is machine-inserted and slightly noisy, but it does convey legitimate cost information.

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 an output schema present, return values needn't be spelled out, and the tool is a single-parameter read. The only material omission is failure behavior for a tweet that turns out not to be an Article, which an agent would plausibly need.

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

Parameters4/5

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

Schema coverage is 100%, so a baseline 3 would apply, but the description adds meaning by clarifying that the tweet ID is the identifier of the Article itself rather than of a separate article resource — resolving an ambiguity the terse schema text ('The tweet ID of the article') leaves open.

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?

A specific verb and resource ('Get the full body of an X Article (long-form post)') with the qualifier that it is keyed by tweet ID. It explicitly distinguishes itself from the closest sibling by naming `get_twitter_tweets` for ordinary tweets, so an agent can route without opening a schema.

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

Usage Guidelines5/5

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

States the precise trigger condition — the tweet links to or is an Article, and the 280-character preview is insufficient — and gives an explicit alternative path for the non-Article case. Nothing is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All AIsa X / Twitter tools Inspect

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