Does this skill require real-time data?

Yes, it leverages Brave Search and Perplexity data retrieval to ensure that Etsy listing counts and Google Trends scores are current at the moment of validation.

How does the skill decide between a GO or SKIP decision?

The skill uses a deterministic script that analyzes specific thresholds: it triggers a SKIP if Etsy listings exceed 100,000 or if Google Trends scores fall below 40. A GO decision typically requires fewer than 50,000 listings and a rising trend direction.

Can I use this for platforms other than Etsy?

While the logic uses Etsy listing counts as a primary benchmark for competition, the resulting data insights and GO/SKIP decisions are highly relevant for any Print-on-Demand or e-commerce platform.

What happens if the data is inconclusive?

If the analysis results in a confidence score below 0.75, the skill automatically escalates the result to a review queue rather than providing a definitive binary decision.

POD Research & Niche Validator

Name: POD Research & Niche Validator
Author: thebird-create

bythebird-create

电子商务解决方案

Validates Print-on-Demand niches using deterministic Etsy competition data and Google Trends to provide data-driven go/no-go decisions.

关于

Pod Research is a specialized Claude Code skill designed for e-commerce entrepreneurs and developers to systematically evaluate product ideas. It automates the analysis of market saturation on platforms like Etsy and gauges consumer interest via Google Trends, applying strict logic to determine if a niche is viable. By providing a binary 'GO' or 'SKIP' decision based on real-time data, it helps users avoid over-saturated markets and focus on high-potential sub-niches with rising interest and low competition.

主要功能

Intelligent sub-niche suggestion generator to identify low-competition entry points.
Confidence-based thresholding with automated escalation for ambiguous market data.
0 GitHub stars
Deterministic GO/SKIP decision engine based on Etsy listing volume and trend stability.
Brand assignment logic to align niche discovery with specific brand identities (LWF vs Touge).
Automated Google Trends analysis with 12-month historical scoring and direction tracking.

使用场景

Validating a new t-shirt design concept before starting the design and production process.
Identifying profitable sub-niches by analyzing modifier keywords and seasonal trend shifts.
Filtering a list of potential product categories to find those with the lowest competition-to-demand ratio.

关于

主要功能

Intelligent sub-niche suggestion generator to identify low-competition entry points.
Confidence-based thresholding with automated escalation for ambiguous market data.
0 GitHub stars
Deterministic GO/SKIP decision engine based on Etsy listing volume and trend stability.
Brand assignment logic to align niche discovery with specific brand identities (LWF vs Touge).
Automated Google Trends analysis with 12-month historical scoring and direction tracking.

使用场景

Validating a new t-shirt design concept before starting the design and production process.
Identifying profitable sub-niches by analyzing modifier keywords and seasonal trend shifts.
Filtering a list of potential product categories to find those with the lowest competition-to-demand ratio.