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Product Recommender
by
fangwei-frank
· GitHub ↗
· v1.0.0
· MIT-0
162
Downloads
0
Stars
1
Active Installs
1
Versions
Install in OpenClaw
/install product-recommender
Description
Intelligent product recommendation engine for retail digital employees. Recommends products based on customer needs, budget, recipient, occasion, preferences...
Usage Guidance
This skill appears coherent for recommending products: it runs a local Python script against a provided knowledge_base.json and uses deterministic filtering/scoring. Before installing/using: 1) Review the complete scripts/recommend.py file (the submission truncated the file end) to confirm the main() function does not perform unexpected I/O or network calls. 2) Ensure the agent will be given only trusted knowledge_base JSON files (don't point --kb at sensitive local files). 3) If you rely on inventory/live API behavior, check how 'stock_status: live_api' is handled elsewhere — the skill assumes live availability if that flag is present. 4) Confirm how 'feature_request' logging is implemented in your environment (the docs mention logging but the visible code doesn't show where it goes). If you want a higher assurance, ask for the full recommend.py file (complete) and any runtime wrapper the agent uses to invoke it so you can verify there are no hidden network endpoints or credential usage.
Capability Assessment
Purpose & Capability
Name/description (product recommendation) match the included SKILL.md and the recommend.py logic: intent extraction, budget/constraint filtering, scoring, upsell logic and presentation. Required resources (a products[] knowledge base) are consistent with the stated purpose; no unrelated credentials or binaries are requested.
Instruction Scope
SKILL.md stays within the recommender domain: it instructs extracting intent signals, running scripts/recommend.py, and returning 3 curated items. It does mention logging 'feature_request' and session state (e.g., upsell_declined) which are not fully implemented in the visible code — minor scope mismatch but not evidence of malicious behavior. The runtime instructions do require a knowledge_base.json path; ensure that path only points to intended product data (the script will read any file given).
Install Mechanism
No install spec (instruction-only with an included script). That is low-risk: nothing is downloaded or installed automatically by the skill.
Credentials
The skill requests no environment variables, credentials, or config paths. The code likewise does not reference secrets or external tokens in the visible portion.
Persistence & Privilege
always is false and the skill does not request persistent system-wide privileges. The script appears to be a transient CLI utility that reads a KB and returns recommendations; it does not modify other skills or system settings in the visible code.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install product-recommender - After installation, invoke the skill by name or use
/product-recommender - 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 Product Recommender?
Intelligent product recommendation engine for retail digital employees. Recommends products based on customer needs, budget, recipient, occasion, preferences... It is an AI Agent Skill for Claude Code / OpenClaw, with 162 downloads so far.
How do I install Product Recommender?
Run "/install product-recommender" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Product Recommender free?
Yes, Product Recommender is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Product Recommender support?
Product Recommender is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Product Recommender?
It is built and maintained by fangwei-frank (@fangwei-frank); the current version is v1.0.0.
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