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product-review-extractor

Extract and analyze product reviews from e-commerce and review sites.

Skill by sandbaseai

IndexedApache-2.0★ 201
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Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/sandbaseai-product-review-extractor

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Extract and analyze product reviews from e-commerce and review sites. Aggregates ratings, identifies common themes in positive and negative feedback, and surfaces actionable product insights from customer voices across platforms.

Use cases: research

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
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Install scripts
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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/product-review-extractor

What's inside

Skill name
product-review-extractor
Description
Extract and analyze product reviews from e-commerce and review sites. Aggregates ratings, identifies common themes in positive and negative feedback, and surfaces actionable product insights from customer voices across platforms.
License
Apache-2.0
Instructions
32 lines in SKILL.md · view on GitHub

Files (2)

  • SKILL.md
  • sandbase-api-map.md · references/

SKILL.md (first lines)

# Product Review Extractor

Extract and analyze product reviews from e-commerce and review sites. Aggregates ratings, identifies common themes in positive and negative feedback, and surfaces actionable product insights from customer voices across platforms. Read [the API map](references/sandbase-api-map.md) 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

- `strale_product_reviews_extract`
- `amazon_bulk_reviews_multi_region`
- `google_maps_bulk_reviews`
- `akta_company_product_reviews`

## 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.

From sandbaseai/sandbase-skills, Apache-2.0.

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Signals

Stars
201
Forks
21
Open issues
1
Last commit (this folder)
Sep 8, 2026 (1 month ago)
Last release
Aug 20, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from sandbaseai

Cite this page

product-review-extractor skill. Agent Mart. https://agentmart.dev/skills/sandbaseai-product-review-extractor (last updated 2026-10-24)