proprietary-data-generator
Create original surveys, benchmarks, and aggregated data nobody else has. Automate data collection for content moats. Triggers on: "create original data", "proprietary data", "survey design", "benchmark study", "original research", "data-driven content", "create a survey", "industry benchmark", "aggregated data", "unique data", "first-party data", "data moat", "generate research data", "create a study", "original statistics", "data nobody else has", "competitive data advantage".
npx skills add Affitor/affiliate-skills --skill proprietary-data-generator --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Proprietary Data Generator Create original surveys, benchmarks, and aggregated data that nobody else has. Proprietary data is the ultimate content moat — competitors can copy your writing style but they can't copy YOUR data. Automates the design and execution framework for data collection that feeds unique content angles. ## Stage S7: Automation & Scale — Generating data at scale requires automation. This skill designs the collection system, not just one data point. Creates repeatable data assets that compound over time. ## When to Use - User wants to create content that can't be replicated by competitors - User asks about "original research", "surveys", "benchmarks", "proprietary data" - User says "data moat", "unique data", "first-party data", "original statistics" - After `content-moat-calculator` identifies the need for differentiated content - User wants to build authority through data-driven content - User wants to create linkable assets that earn backlinks naturally ## Input Schema ```yaml niche: string # REQUIRED — topic area for data collection # e.g., "AI video tools", "affiliate marketing" data_type: string # OPTIONAL — "survey" | "benchmark" | "aggregation" | "case_st
- Stage
- When to Use
- Input Schema
- Workflow
- Step 1: Identify Data Opportunity
- Step 2: Design Data Collection
- Step 3: Create Collection Assets
- Step 4: Design Automation
- Step 5: Self-Validation
- Output Schema
- Output Format
- Error Handling
- Examples
- Revenue & Action Plan
What does the proprietary-data-generator skill do?
Create original surveys, benchmarks, and aggregated data nobody else has. Automate data collection for content moats. Triggers on: "create original data", "proprietary data", "survey design", "benchmark study", "original research", "data-driven content", "create a survey", "industry benchmark", "aggregated data", "unique data", "first-party data", "data moat", "generate research data", "create a study", "original statistics", "data nobody else has", "competitive data advantage".
How do I install it?
Run `npx skills add Affitor/affiliate-skills --skill proprietary-data-generator --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From Affitor/affiliate-skills, a repository with 586 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.