Four tools with complete Zod schemas and basic descriptions. All tools follow verb_noun naming (people-also-ask, google-autocomplete, forums, semantic-keywords). Schemas include proper type constraints (minLength, length, defaults). However, descriptions are generic (34-56 chars, below the 50-200 char LLM-optimized baseline) and lack context about WHEN to use each tool or what distinguishes them. Parameter descriptions are present but minimal. No output schema documentation. Error handling returns plain text without recovery guidance. No pagination support despite tools returning lists. Missing idempotency hints for read-only operations.
Get Reddit and Quora questions for a given query
Get Google Autocomplete suggestions for a given query
Get People Also Ask questions for a given query
Get Semantic (similar, related) keywords for a given query
Descriptions too short (34-56 chars) to guide LLM tool selection. Lack context about when to use each tool vs. alternatives. Baseline for LLM-optimized descriptions is 50-200 chars.
No output schema documented. LLMs cannot plan downstream calls or extract structured data. All tools return plain text in a generic content array.
No pagination support. Tools return unbounded lists without limit, offset, or cursor parameters. Large result sets will blow context windows.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 50 | 2026-07-28+ | v2 |
Error handling returns generic 'Failed to retrieve data' without recovery guidance. LLM cannot determine if error is retryable, user-fixable, or fatal.
Parameter descriptions lack format/constraint details. E.g., 'Two-letter language code' should specify 'ISO 639-1 format (e.g., en, fr, es)' and note that invalid codes will fail.