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Text to Emoji

TexttoEmoji
Read-only

Text to Emoji: Text to Emoji converts plain text strings into matching emoji representations. Send any word or phrase and receive the corresponding emoji characters. (Cost: 2 credits)

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": {
      "text": "<text>"
    },
    "name": "TexttoEmoji"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYesThe text you want converted into emojis

Output Schema

NameRequiredDescriptionDefault
dataNo
errorNoError message, null on success
statusNo"ok" on success

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.8/5.0
Behavior3/5

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

Annotations already cover readOnly/openWorld/destructive, so the only added behavioral fact is the 'Cost: 2 credits' note, which is genuinely useful for a metered API. However, the description says nothing about how gaps in emoji coverage are handled or what the output looks like structurally.

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

Conciseness3/5

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

Only three short sentences, but the first two repeat the tool name and title verbatim ('Text to Emoji: Text to Emoji converts...') without adding information. The cost note is buried at the end in parentheses rather than integrated into a clear statement of behavior.

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

Completeness3/5

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

An output schema exists, so return-value explanation is not required, and the single parameter is covered. What is missing is the mapping semantics that make this tool's behavior predictable — how words without emoji equivalents are treated — plus any positional usage guidance among emoji siblings.

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% and there is only one parameter, so the schema already fully documents 'text'. 'Send any word or phrase' adds marginal framing but no format, length, or language constraints beyond what the schema states.

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?

The description states the verb and resource ('converts plain text strings into matching emoji representations'), but it largely restates the tool name three times. It never explains the mapping mechanism (per word, per character, what happens to unmapped words) and never distinguishes it from EmojiDecorator or EmojiLookup, which an agent would plausibly confuse it with.

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

Usage Guidelines2/5

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

There is no when-to-use guidance at all. Given siblings like EmojiDecorator, EmojiLookup and TextStyler, the description should say which one to pick for translation vs decoration vs lookup, but it offers nothing.

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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