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OpenTweet MCP Server

OpenTweet MCP Server

Official
by opentweetio
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

opentweet_remove_from_evergreen

DestructiveIdempotent

Remove a post from the evergreen pool, converting it to a regular draft for further editing and scheduling.

Instructions

Remove a post from the evergreen pool. The post is converted back to a regular draft, not deleted.

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": "opentweet_remove_from_evergreen"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesThe evergreen post ID to remove from pool

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.0

TDQS

A4/5.0
Behavior4/5

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

Annotations provide idempotent and destructive hints. The description adds behavioral context by stating the post is 'converted back to a regular draft, not deleted,' which clarifies the exact state change and avoids misunderstanding. No contradiction with 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 short sentences with no unnecessary words. It front-loads the action and explains the crucial nuance about not deleting, making it highly efficient.

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?

Given the simplicity of the tool (one parameter, no output schema), the description is sufficient. It explains the input and the effect, leaving no ambiguity. A slightly higher score might be warranted but is limited by the lack of any return value information.

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 parameter 'id' is already described in the input schema as 'The evergreen post ID to remove from pool.' The tool description does not add further semantics, but schema coverage is 100%, meeting the baseline.

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 action: 'Remove a post from the evergreen pool.' It uses a specific verb and resource, and distinguishes from deletion by noting the post is converted back to a regular draft. This differentiates it from sibling tools like opentweet_delete_tweet.

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 description explains the effect but does not explicitly state when to use this tool versus alternatives. It implies the use case (removing from evergreen) but lacks guidance on when not to use it or a comparison with similar tools.

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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