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Publish draft post

publish_draft

Publish an approved draft to X (Twitter) via API v2. Supports threads, polls, media, quotes, community posts, and paid partnerships. Returns live post URLs.

Instructions

Publish an approved draft to X via the X API v2. Supports threads, polls, media, quotes, community posts, and paid partnership. Fails if the draft has not been approved yet (unless approval is disabled in config). Returns the live post URL(s).

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": {
      "id": "<id>"
    },
    "name": "publish_draft"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes	Draft id.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Jul 31, 2026

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the API used (X API v2), supported content types, failure behavior for unapproved drafts, a configuration dependency (unless approval is disabled), and the return value (live post URL(s)). This is solidly transparent, though it omits potential side effects like draft state changes after publishing.

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 exactly two sentences: the first gives the core purpose, the second packs in capabilities, failure conditions, and return value. Every sentence earns its place with no redundancy or 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?

For a simple one-parameter tool with no output schema, the description adequately covers inputs, behavior, and outputs. It mentions supported feature types and edge-case failure, making it mostly complete. It could have mentioned what happens to the draft after publishing, but this is a minor omission.

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?

The single 'id' parameter is fully described in the schema as 'Draft id', and the tool description does not add any extra semantics beyond that. Since schema coverage is 100%, a baseline of 3 is appropriate.

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 clearly states the tool 'publish[es] an approved draft to X via the X API v2', with a specific verb (publish) and resource (draft). It distinguishes from sibling tools like list_drafts or approve_draft by focusing on the action of publishing, and even lists supported content types, reinforcing its unique role.

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?

It implicitly defines the usage context by noting the draft must be approved, and explicitly states it 'fails if the draft has not been approved yet', making the prerequisite evident. While it doesn't name alternative tools, the approval requirement signals that approve_draft should be used first, and the lack of mention of alternatives is a minor gap.

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