---

name: product-intelligence description: "Research products across Amazon, Google Shopping, and Xiaohongshu to understand pricing, reviews, market positioning, and consumer sentiment. Covers competitive product analysis, pricing benchmarks, feature comparison, and customer satisfaction signals."

Product Intelligence

Research products across Amazon, Google Shopping, and Xiaohongshu to understand pricing, reviews, market positioning, and consumer sentiment. Covers competitive product analysis, pricing benchmarks, feature comparison, and customer satisfaction signals. Read the API map before selecting a capability.

Call SandBase capabilities

Use the capability identifiers below as discovery hints, not MCP tool names. Find the matching endpoint with sandbase_discover(q: "<provider and capability>"); use its returned name in sandbase_inspect(name: "<returned name>"). Read inputSchema, pricing, and execute_as, then call sandbase_run using execute_as.arguments.name and schema-defined arguments. If a run_id is returned, poll sandbase_run_get(run_id: "<returned run_id>") within the task budget until completed or failed; report pending or failed runs without resubmitting them automatically.

Capability identifiers

• amazon_bulk_product_details
• amazon_bulk_reviews_multi_region
• google_shopping_bulk_products
• xiaohongshu_app_v2_search_products
• xiaohongshu_app_v2_product_reviews
• strale_product_reviews_extract

Workflow

1. Understand the user's research question, target, and context.
2. Resolve each selected capability with sandbase_discover, then inspect the returned name with sandbase_inspect to confirm the schema and pricing.
3. Follow execute_as with sandbase_run; collect async results with sandbase_run_get as described above.
4. Synthesize findings into a clear, evidence-backed answer.
5. Cite sources, note evidence gaps, and separate observations from interpretations.

Guidelines

• Always call sandbase_inspect 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.