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Product Research
by
beyondbright
· GitHub ↗
· v1.0.0
· MIT-0
68
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0
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0
Active Installs
1
Versions
Install in OpenClaw
/install walter-product-research
Description
Conducts Amazon product research by analyzing market size, competition, profit margins, competitors, and risks to provide GO/NO-GO recommendations.
Usage Guidance
This skill implements an Amazon product-research workflow but relies on an external 'unified_data_layer_v2' and SellerSprite API. Before installing or running it: (1) ask the author to declare required environment variables (API keys/tokens) and document endpoints; (2) request and review the unified_data_layer_v2 and sellersprite_mcp source to confirm where requests go and how credentials are used; (3) note the code alters sys.path to import modules from parent directories — run it in a sandbox or isolated environment to avoid importing unexpected code; (4) do not provide production API credentials until you verify the data-layer code and the remote endpoints; and (5) if you can't review the missing modules, prefer a safer alternative or ask the publisher to bundle audited connectors and declare required env vars in the skill manifest.
Capability Analysis
Type: OpenClaw Skill
Name: walter-product-research
Version: 1.0.0
The skill bundle provides legitimate Amazon product research functionality, including market analysis, profit calculation, and competitor discovery. The code in `scripts/product_research.py` and `scripts/test_logic.py` is well-structured, lacks any signs of data exfiltration or malicious execution, and uses a modular data layer for API interactions consistent with its stated purpose.
Capability Assessment
Purpose & Capability
The skill claims to perform Amazon product research and the code implements that using a data layer and SellerSprite API. However the package metadata declares no required environment variables or credentials even though the SKILL.md and code depend on an external data layer (unified_data_layer_v2) and SellerSprite API access. Not declaring the needed API credentials is an inconsistency.
Instruction Scope
SKILL.md describes a bounded analysis workflow and the code follows it. However the runtime code injects a sys.path entry that points three directories up into a 'scripts' folder to import unified_data_layer_v2, which means the skill will try to import code from outside its own bundle at runtime — this increases the attack surface and can cause the agent to execute unexpected code. The instructions do not disclose where the data layer will send network requests or which credentials it expects.
Install Mechanism
There is no install spec (instruction-only with included code files). Nothing is downloaded at install time. Risk comes from runtime imports and the external data-layer dependency rather than an installer.
Credentials
No environment variables or primary credential are declared, yet the SKILL.md lists 'SellerSprite API access' as a dependency and the code calls external APIs via a data layer. This mismatch means the skill will likely require API keys/credentials that are not declared or explained, which is disproportionate and opaque.
Persistence & Privilege
The skill does not request persistent/always-on presence (always:false) and does not modify agent/system configuration in the provided code. The main privilege-related risk is autonomous runtime network access via the external data layer, not persistent installation.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install walter-product-research - After installation, invoke the skill by name or use
/walter-product-research - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
walter-product-research 1.0.0
- 首次发布亚马逊选品调研工具。
- 支持全流程：快速扫描、市场分析、利润测算、竞品发现、风险评估。
- 输出决策报告（GO/NO-GO）、市场和竞品关键数据、详细分析链路。
- 适用于“这个想法能不能做”等场景。
- 依赖统一数据层和SellerSprite API。
Metadata
Frequently Asked Questions
What is Product Research?
Conducts Amazon product research by analyzing market size, competition, profit margins, competitors, and risks to provide GO/NO-GO recommendations. It is an AI Agent Skill for Claude Code / OpenClaw, with 68 downloads so far.
How do I install Product Research?
Run "/install walter-product-research" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Product Research free?
Yes, Product Research is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Product Research support?
Product Research is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Product Research?
It is built and maintained by beyondbright (@beyondbright); the current version is v1.0.0.
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