Skip to main content
Glama

x402-ai-tweet

AI Tweet: Generate a tweet with AI.

Input Schema

NameRequiredDescriptionDefault
textNo
toneNo
topicNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • removedInput schema / properties / text / description
      Removed value: -"Text to process"
    • removedInput schema / properties / tone / description
      Removed value: -"Tone to process"
    • removedInput schema / properties / topic / description
      Removed value: -"Topic to process"
  2. Changed1 schema field changed
    • addedInput schema / properties / text
      Added value: +{
      +  "description": "Text to process",
      +  "type": "string"
      +}
  3. First observed

TDQS

D1.6/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full behavioral burden and delivers nothing: no mention of permissions, rate limits, cost/payment (these x402 tools are paid), or whether generation is deterministic. "With AI" is filler rather than behavioral disclosure.

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

Conciseness2/5

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

It is short and front-loaded, but the brevity is under-specification rather than efficiency: the "AI Tweet:" prefix restates the tool name and "with AI" is redundant for an AI tool, leaving only a few meaningful words.

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

Completeness1/5

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

With no annotations, no output schema, and three fully undocumented parameters, the definition is inadequate for an agent to invoke the tool correctly. Nothing is said about inputs, outputs, or how the result is shaped.

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

Parameters1/5

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

All three parameters (text, tone, topic) have 0% schema description coverage, and the description never names or explains them. It is unclear whether text is a seed/draft, whether topic and text are alternatives or complements, or what values tone accepts — none of which the schema clarifies.

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

Purpose3/5

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

It states a concrete verb and resource ("generate a tweet"), so the purpose is not truly vague, but the leading "AI Tweet:" simply re-echoes the tool name and "with AI" adds no information. It gives no differentiation from the sibling x402-ai-tweet-thread, which an agent would need to choose between.

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

Usage Guidelines1/5

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

There is no guidance at all on when to use this tool, when not to, or how it differs from the very similar sibling x402-ai-tweet-thread. The agent is left to guess from the name alone.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources