Review Intelligence
review_intelligenceReturns a research framework, not the finished analysis: the procedure, output schema and quality rubric for mining public reviews for signal — a complaint taxonomy, theme extraction, sentiment trajectory over time, the differentiators customers actually cite, and red flags for a buyer. It does not read any review itself.. This tool fetches no data; the calling model runs the procedure with its own web search and produces the result.
Example invocations:
"Mine the reviews for Al's Breakfast in Minneapolis for real patterns, not just a star rating"
"Perfect Image Salon in Wichita has a 4.6 average — check whether that's stable or masking a bad last 90 days"
"I'm evaluating The Anchor Room (bar) in Saint Paul, MN as a buyer — what do the reviews show about staffing turnover or an ownership change that the rating alone doesn't?"
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | Category if known — helps set expectations for review volume/velocity norms. | |
| city_metro | Yes | City + state/region, e.g. 'Wichita, KS' — disambiguates same-named businesses. | |
| business_name | Yes | The business's name as it appears on its own signage/website. |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| tool | Yes | ||
| notice | No | Present ONLY when the request was denied by usage policy instead of executed. When present, every other field is an empty placeholder and must not be reported as a framework. | |
| caveats | Yes | ||
| subject | No | ||
| framework | Yes | ||
| output_schema | Yes | ||
| quality_rubric | Yes | ||
| research_procedure | Yes |