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Retail Knowledge
by
fangwei-frank
· GitHub ↗
· v1.0.0
· MIT-0
187
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Install in OpenClaw
/install retail-knowledge
Description
Product knowledge Q&A and policy lookup for retail digital employees. Answers customer and staff questions about products, store policies, promotions, FAQs,...
Usage Guidance
This skill appears coherent and low-risk: it searches a local knowledge_base.json and constructs answers from that KB. Before installing, confirm (1) the source and contents of the knowledge base (who can edit the JSON file), (2) where the skill's "internal" logs will be stored (the SKILL.md mentions logging but doesn't specify the storage/retention), and (3) the other referenced setup/hand-off skills (retail-agent-setup, product-recommender, inventory-query, complaint-handler) to ensure they are trustworthy. If you plan to run kb_search.py, ensure the KB file path you supply is the intended, access-controlled file and not a general system path.
Capability Analysis
Type: OpenClaw Skill
Name: retail-knowledge
Version: 1.0.0
The retail-knowledge skill bundle is a standard implementation for a retail Q&A agent. It includes a Python script (scripts/kb_search.py) for searching a local JSON knowledge base using weighted keyword matching and documentation (SKILL.md and references/) that guides the agent on answer construction and persona management. No malicious behaviors, data exfiltration, or harmful instructions were found.
Capability Assessment
Purpose & Capability
Name/description map to a KB-driven Q&A assistant. The included kb_search.py and the SKILL.md both focus on searching a local knowledge_base.json and constructing grounded answers; nothing in the bundle requires access to unrelated services or credentials.
Instruction Scope
Runtime instructions stay within the stated scope (classify queries, consult KB, build answers, hand off to other retail skills when appropriate). One small ambiguity: SKILL.md says to "log the query internally for Step 12 gap digest" but doesn't define the log location or retention — this is an operational detail to clarify, not an evidence of malicious behavior.
Install Mechanism
No install spec — instruction-only with a single Python script. The script is small, local, and does not fetch external artifacts or write arbitrary files; risk from installation is minimal.
Credentials
The skill declares no required environment variables, no primary credential, and no config paths. The code only reads a KB file passed as an argument; it does not access other environment secrets or network endpoints.
Persistence & Privilege
always is false and the skill is user-invocable with normal autonomous invocation allowed. The skill does not request persistent system-wide privileges or modify other skills' config.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install retail-knowledge - After installation, invoke the skill by name or use
/retail-knowledge - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
first release
Metadata
Frequently Asked Questions
What is Retail Knowledge?
Product knowledge Q&A and policy lookup for retail digital employees. Answers customer and staff questions about products, store policies, promotions, FAQs,... It is an AI Agent Skill for Claude Code / OpenClaw, with 187 downloads so far.
How do I install Retail Knowledge?
Run "/install retail-knowledge" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Retail Knowledge free?
Yes, Retail Knowledge is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Retail Knowledge support?
Retail Knowledge is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Retail Knowledge?
It is built and maintained by fangwei-frank (@fangwei-frank); the current version is v1.0.0.
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