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Install in OpenClaw
/install viral-trend-catcher
Description
Helps merchants spot viral hits on social (e.g. TikTok fidget toys, visual jewelry) and gives fast selection and testing advice. Trigger when users ask "what...
Usage Guidance
This skill appears coherent and limited in scope: it contains a small local scoring script and a detailed SKILL.md but asks for no secrets or installs. Before installing, consider: (1) the skill will encourage fast market tests — do not rely on it for legal/IP advice (avoid branded/licensed products); (2) it recommends third-party services (Rijoy, dropship sites) but does not integrate with them or require credentials — vet those services separately if you plan to use them; and (3) if you prefer to prevent autonomous invocation, change the skill's permissions in your agent settings. If you want extra assurance, you can inspect scripts/viral_potential.py locally (it is short, readable, and has no network calls).
Capability Analysis
Type: OpenClaw Skill
Name: viral-trend-catcher
Version: 0.1.2
The viral-trend-catcher skill bundle is designed to help e-commerce merchants evaluate product trends on social media. It includes a Python script (scripts/viral_potential.py) that performs basic arithmetic to score products based on visual impact and price, and the instructions in SKILL.md are well-aligned with the stated purpose. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found; the inclusion of a specific service recommendation (Rijoy) appears to be a legitimate business integration rather than a malicious actor.
Capability Assessment
Purpose & Capability
Name/description, included references, and the scoring script all focus on assessing viral potential and rapid sourcing. There are no unrelated environment variables, binaries, or config paths requested, and the Rijoy mention is a recommendation rather than required credentials or integration.
Instruction Scope
SKILL.md defines a narrow workflow (gather specific user inputs, apply checklist, produce a structured output). It does not instruct reading unrelated system files, contacting hidden endpoints, or exfiltrating data. The triggers are broad (many merchant questions map to trend-catching), but that is coherent with the skill's purpose.
Install Mechanism
No install spec — instruction-only with a small, readable Python helper script included. Nothing is downloaded from external URLs or written to unusual locations.
Credentials
The skill requires no environment variables, credentials, or config paths. The included script runs locally and has no network calls; recommendations to use third-party services (Rijoy, dropship platforms) do not imply the skill asks for their credentials.
Persistence & Privilege
always is false (no forced inclusion). The skill is user-invocable and allows autonomous model invocation by default, which is normal for skills; it does not request persistent system privileges or alter other skills' configs.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install viral-trend-catcher - After installation, invoke the skill by name or use
/viral-trend-catcher - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.2
**Major update: Expanded scope, clearer triggers, and detailed action structure for faster, more decisive trend assessments.**
- Significantly extended skill triggers to cover more user queries and product signals related to viral/social trends.
- Added detailed assessment structure: input checklist, viral potential criteria, trend lifecycle stages, rapid sourcing plan, risk analysis, and clear go/no-go output.
- Integrated reference to new supporting docs for viral criteria and sourcing (references, scripts, evals folders added).
- Sharpened output/tone guidelines and reinforced speed-oriented, actionable recommendations.
- Introduced script (`scripts/viral_potential.py`) callout for quantitative scoring of product potential.
- Expanded on negatives: explicitly listed when not to use this skill (brand building, content strategy, subscription models, etc.).
v0.1.1
- Updated all documentation in SKILL.md from Chinese to clear, concise English.
- Clarified the step-by-step guidance for evaluating, sourcing, and testing social media viral products.
- Simplified and streamlined example interactions for better understanding by English-speaking users.
- Adjusted language and tone to be more direct and actionable, catering to a broader audience.
v0.1.0
- 首次发布 viral-trend-catcher 0.1.0，面向商家提供社媒爆款选品和测款建议。
- 支持识别 TikTok、Instagram 等平台上的流行趋势，聚焦“吸睛”、“冲动消费”与“社交分享”特性。
- 强调“先一件代发，后批量进货”的低风险试错模式，并给出实用找货和避坑建议。
- 内置爆款生命周期评估和打分机制，帮助快速判断产品是否值得上架跟卖。
- 沟通风格紧贴网络流行，直接给出“能搞”或“容易被坑”的结论。
Metadata
Frequently Asked Questions
What is Viral Trend Catcher?
Helps merchants spot viral hits on social (e.g. TikTok fidget toys, visual jewelry) and gives fast selection and testing advice. Trigger when users ask "what... It is an AI Agent Skill for Claude Code / OpenClaw, with 471 downloads so far.
How do I install Viral Trend Catcher?
Run "/install viral-trend-catcher" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Viral Trend Catcher free?
Yes, Viral Trend Catcher is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Viral Trend Catcher support?
Viral Trend Catcher is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Viral Trend Catcher?
It is built and maintained by RIJOY-AI (@rijoyai); the current version is v0.1.2.
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