# Review Aggregator

> Aggregate and analyze product and business reviews from Google Maps, Amazon, Akta, and Xiaohongshu. Cross-platform review intelligence including rating patterns, common themes, competitive comparison, and customer satisfaction trends.

- Skill: `sandbaseai-sandbase-skills/review-aggregator` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add sandbaseai-sandbase-skills/review-aggregator`
- Raw SKILL.md: https://api.skillmd.com/api/skills/sandbaseai-sandbase-skills/review-aggregator/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Research & Search
- Author: sandbaseai (https://skillmd.com/u/sandbaseai-sandbase-skills)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/sandbaseai-sandbase-skills/review-aggregator

---


# Review Aggregator

Aggregate and analyze product and business reviews from Google Maps, Amazon, Akta, and Xiaohongshu. Cross-platform review intelligence including rating patterns, common themes, competitive comparison, and customer satisfaction trends. Read [the API map](references/sandbase-api-map.md) before selecting a capability.

## Call SandBase capabilities

For every selected tool, call `sandbase_describe_tool` first and use only arguments in its current input schema. Then call `sandbase_call_tool` with the exact `tool_name`.

## Available Tools

- `google_maps_bulk_reviews`
- `amazon_bulk_reviews_multi_region`
- `akta_company_product_reviews`
- `xiaohongshu_app_v2_product_reviews`

## Workflow

1. Understand the user's research question, target, and context.
2. Call `sandbase_describe_tool` for each selected tool to confirm parameter schema.
3. Call `sandbase_call_tool` with the exact tool_name and schema-defined arguments.
4. Synthesize findings into a clear, evidence-backed answer.
5. Cite sources, note evidence gaps, and separate observations from interpretations.

## Guidelines

- Always call `sandbase_describe_tool` before using any capability.
- Cite sources and preserve attribution (URLs, usernames, dates, metrics).
- Separate factual observations from analysis and recommendations.
- If data is unavailable, note the gap and continue with available evidence.
- Read-only research only. Never take actions on platforms.