immit dictionary

Report a missing word

report_missing_word

Tell immit that a real word has no entry, so a lexicographer adds one. Call it when lookup_word and search_words both miss a word a person asked about and you are confident the word exists in that language: a headword in its dictionary form, never an inflected form, a typo or a proper noun. context is optional, the sentence the word came from or what the person wanted to know. The report is read by a person; nothing is added on the spot, so answer the person from what you know and say the dictionary lacks the word.

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": {
      "lang": "<lang>",
      "text": "<text>"
    },
    "name": "report_missing_word"
  }
}

Input Schema

Name	Required	Description
`lang`	Yes	The language of the word: eng for English, jpn for Japanese
`text`	Yes	The missing word in its dictionary form
`context`	No	Where the word came up, or what the person asked

Output Schema

Name	Required	Description	Default
`received`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 7, 2026

TDQS

A4.7/5.0

Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does most of it well: the report is human-reviewed, nothing is added on the spot, so the agent must answer from its own knowledge. It does not say whether duplicate reports are accepted, what confirmation is returned, or any rate limits, which keeps it short of a 5 for a mutation-like submission tool.

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?

Front-loaded with the purpose, then the call condition, then the constraint, then the follow-up behavior. No sentence is redundant and nothing is buried in a trailing clause.

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

Completeness5/5

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

For a three-parameter reporting tool with an output schema already defined, the description covers the purpose, the trigger, form constraints, the human-review latency, and how the agent should respond to the user in the meantime. Nothing an agent needs in order to call it correctly is missing.

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 the baseline is 3, but the description adds real meaning: text must be a headword in dictionary form and explicitly not an inflected form, typo, or proper noun, and context is clarified as the source sentence or the person's question. This adds constraints the schema alone does not express.

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 uses a specific verb+resource ('Tell immit that a real word has no entry') and immediately explains the downstream effect (a lexicographer adds one). It also names the two sibling tools it must not be confused with, so an agent can distinguish it without opening any 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?

It gives an explicit trigger ('when lookup_word and search_words both miss a word a person asked about'), an explicit confidence condition, and exclusions ('never an inflected form, a typo or a proper noun'). It also states what to do instead of waiting for a result, which is the practical alternative behavior.

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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