Single tool 'get_text_length' has a basic description in Japanese but lacks English documentation and proper schema structure. The tool is defined via FastMCP decorator with minimal metadata. Input schema is present (text: string) but lacks formal JSON Schema with type/description separation. No output schema documented. Description is 120 chars but mixes docstring format with parameter docs, not optimized for LLM selection. No error handling guidance, no parameter constraints, no recovery paths. Naming is acceptable (verb_noun) but description quality is below baseline (194 chars avg for A+ tools). Tool is READ_ONLY but lacks explicit annotation.
テキストの文字数を取得するツール Args: text (str): 文字数を取得したいテキスト Returns: int: テキストの文字数
Description is in Japanese only; LLM clients expect English. Baseline A+ tools have 194-char descriptions optimized for LLM selection; this is 120 chars and mixes docstring with parameter docs.
No output schema documented. LLMs cannot plan downstream calls or extract results without knowing return type structure. Baseline: 100% of A+ tools have documented return types.
Input schema lacks formal JSON Schema structure. Parameter 'text' has description but no explicit type declaration in schema metadata. Schema score capped at 40 due to incomplete formalization.
No error handling guidance. Tool strips quotes/newlines but provides no error messages if input is invalid. LLMs cannot self-correct without actionable error responses.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 39 | 2026-07-28+ | v2 |
READ_ONLY risk classification present but no tool annotation (readOnlyHint) in schema. Spec 2026-07-28 supports tool annotations for safety hints.