AI-powered toolkit for global trend intelligence, product research, and e-commerce opportunity reports.
TrendPilot AI is a license-safe starter kit for builders, marketers, researchers, and e-commerce operators who want to design AI-powered trend intelligence workflows using public data sources, prompt templates, report templates, scoring models, pseudo-workflows, integration guides, and a lightweight local Python execution layer.
It does not copy or redistribute third-party project code.
Instead, it organizes original documentation, prompts, templates, workflows, schemas, safe integration guidance, and small executable examples to help users build responsible AI-powered trend research systems.
TrendPilot AI helps users design workflows that can:
- Monitor public trend signals
- Analyze e-commerce product opportunities
- Summarize marketplace, social, community, review, and news signals
- Score product ideas with a transparent framework
- Generate daily or weekly trend reports
- Create Telegram or email digests
- Store research records in Google Sheets
- Add human review before publishing or monetizing reports
- Run local CSV validation, product scoring, and Markdown report generation through a small Python CLI
TrendPilot AI is not:
- An auto-money system
- A guaranteed profit system
- A scraping farm
- A spam automation tool
- A fake engagement tool
- A fake review generator
- A private data scraper
- A platform bypass toolkit
- A trading bot
- A financial prediction system
- A replacement for legal, compliance, or business due diligence
This project is for research, education, workflow planning, and responsible market intelligence.
If you find this project useful, consider buying me a coffee. ☕
Public Trend Sources
↓
Data Collection Layer
↓
AI Trend Analysis
↓
Product Opportunity Scoring
↓
Risk Check
↓
Human Review
↓
Source Log / Google Sheets
↓
Report Templates
↓
Telegram / Email / Notion / PDF
trendpilot-ai/
├── README.md
├── LICENSE
├── ATTRIBUTION.md
├── DISCLAIMER.md
├── SECURITY.md
├── UPGRADE_NOTES.md
├── pyproject.toml
├── setup.py
├── requirements.txt
├── requirements-dev.txt
├── requirements-integrations.txt
├── Makefile
├── docker-compose.yml
├── .env.example
├── .github/
│ ├── FUNDING.yml
│ ├── workflows/
│ │ ├── ci.yml
│ │ └── publish.yml
│ ├── ISSUE_TEMPLATE/
│ └── PULL_REQUEST_TEMPLATE.md
├── trendpilot/
│ ├── cli.py
│ ├── scoring.py
│ ├── records.py
│ ├── report.py
│ └── fields.py
├── tests/
│ ├── test_scoring.py
│ ├── test_records.py
│ └── test_report.py
├── docs/
│ ├── architecture.md
│ ├── data-sources.md
│ ├── tool-map.md
│ ├── workflow-design.md
│ ├── execution-layer.md
│ ├── publishing.md
│ ├── compliance.md
│ ├── license-risk-matrix.md
│ └── monetization.md
├── prompts/
│ ├── trend-analysis-prompt.md
│ ├── product-scoring-prompt.md
│ ├── competitor-summary-prompt.md
│ ├── review-pain-point-prompt.md
│ ├── content-angle-prompt.md
│ └── risk-check-prompt.md
├── templates/
│ ├── daily-trend-report.md
│ ├── product-opportunity-scorecard.md
│ ├── ecommerce-market-report.md
│ ├── weekly-market-brief.md
│ ├── competitor-snapshot.md
│ ├── source-log-template.csv
│ └── telegram-digest-template.md
├── schemas/
│ ├── trend-signal.schema.json
│ ├── product-score.schema.json
│ └── report-record.schema.json
├── examples/
│ ├── sample-daily-report-en.md
│ ├── sample-daily-report-cn.md
│ ├── sample-product-score.csv
│ ├── sample-source-log.csv
│ └── python/
│ ├── README.md
│ ├── daily_report_generator.py
│ └── score_product_idea.py
├── integrations/examples/
│ ├── firecrawl_fetch.py
│ └── google_sheets_append.py
├── workflows/
│ ├── README.md
│ ├── n8n-daily-trend-intelligence.pseudo.json
│ ├── n8n-community-trend-monitor.pseudo.json
│ ├── n8n-google-sheets-output.pseudo.json
│ └── n8n-telegram-digest.pseudo.json
└── integrations/
├── n8n.md
├── firecrawl.md
├── dify.md
├── browser-use.md
└── google-sheets.md
Start here:
Use one of the pseudo-workflows:
- Daily Trend Intelligence Workflow
- Community Trend Monitor Workflow
- Google Sheets Output Workflow
- Telegram Digest Workflow
These files are pseudo-workflows. They are not real n8n export files and should not be imported directly into n8n.
Core prompts:
- Trend Analysis Prompt
- Product Scoring Prompt
- Competitor Summary Prompt
- Review Pain Point Prompt
- Content Angle Prompt
- Risk Check Prompt
Use:
- Source Log CSV Template
- Trend Signal Schema
- Product Score Schema
- Report Record Schema
- Google Sheets Integration Guide
Use:
- Daily Trend Report Template
- Weekly Market Brief Template
- E-commerce Market Report Template
- Product Opportunity Scorecard
- Competitor Snapshot Template
- Telegram Digest Template
Use the examples to understand the expected output style and field structure:
The examples use fictional sample data for structure demonstration only.
Use the Python examples to generate a simple Markdown report or score a product idea locally:
These scripts use only the Python standard library. They do not scrape websites, call external APIs, or send messages.
python -m pip install -r requirements.txt
python -m trendpilot validate --input examples/sample-source-log.csv
python -m trendpilot report --input examples/sample-source-log.csv --output examples/generated-daily-report.md --limit 5You can also use Makefile shortcuts:
make install
make test
make validate
make report
make scoreDevelopment shortcuts:
make install
make dev
make ciThe score shortcut uses examples/sample-product-score-input.json, so the Makefile stays readable while the CLI remains scriptable.
GitHub Actions CI is available at .github/workflows/ci.yml and runs linting, unit tests, schema sample validation, and CLI smoke tests.
For details, see Execution Layer.
For optional package publishing details, see Publishing Guide.
Optional integration examples are available in integrations/examples.
These examples require your own credentials and are not enabled by default:
- Firecrawl URL fetch example
- Google Sheets append example
- local n8n runtime through
docker-compose.yml
TrendPilot AI uses one consistent record structure across templates, workflows, and integrations.
record_id
source_type
source_name
source_url
collection_date
publication_date
region
category
keyword
product_name
trend_signal
evidence_summary
target_audience
pain_point
content_angle
price_signal
competition_signal
risk_note
risk_level
confidence
opportunity_score
next_action
review_status
reviewer_note
Important:
risk_note = human-readable explanation of the risk
risk_level = standardized risk category
Recommended risk level values:
Low
Medium
High
Avoid
Unknown
Recommended confidence values:
Low
Medium
High
Recommended review status values:
Draft
Needs Review
Approved
Rejected
Watchlist
TrendPilot AI uses a simple 1-5 scoring model.
Positive factors:
Demand Signal
Social Visibility
Price Potential
Supplier Availability
Differentiation Potential
Negative factors:
Competition Level
Shipping Difficulty
Compliance Risk
Formula:
Opportunity Score =
Demand Signal
+ Social Visibility
+ Price Potential
+ Supplier Availability
+ Differentiation Potential
- Competition Level
- Shipping Difficulty
- Compliance Risk
Score interpretation:
| Final Score | Interpretation |
|---|---|
| 12 or higher | Strong candidate for deeper research |
| 8 to 11 | Test carefully |
| 4 to 7 | Watchlist |
| Below 4 | Avoid unless stronger evidence appears |
Important:
A high score does not guarantee sales, profit, or product success.
Core documentation:
- System Architecture
- Data Sources
- Tool Map
- Workflow Design
- Execution Layer
- Compliance Guide
- License Risk Matrix
- Monetization Guide
Prompt library:
- Trend Analysis Prompt
- Product Scoring Prompt
- Competitor Summary Prompt
- Review Pain Point Prompt
- Content Angle Prompt
- Risk Check Prompt
Report and research templates:
- Daily Trend Report Template
- Weekly Market Brief Template
- E-commerce Market Report Template
- Product Opportunity Scorecard
- Competitor Snapshot Template
- Telegram Digest Template
- Source Log CSV Template
Structured data schemas:
Sample outputs and sample CSV records:
Lightweight Python examples:
Important:
The examples use fictional sample data.
They are for workflow testing and format demonstration only.
They do not validate real market demand, sales potential, or profit.
The Python scripts do not scrape websites, call external APIs, or automate outreach.
Pseudo-workflow blueprints:
- Workflows Overview
- Daily Trend Intelligence
- Community Trend Monitor
- Google Sheets Output
- Telegram Digest
Important:
These workflow files are planning templates only.
They are not real n8n workflow exports.
They should not be imported directly into n8n.
External tool integration guides:
- n8n Integration Guide
- Firecrawl Integration Guide
- Dify Integration Guide
- Browser-use Integration Guide
- Google Sheets Integration Guide
TrendPilot AI does not include or redistribute third-party source code.
These tools are referenced as external tools only.
TrendPilot AI workflows should:
- Use public and legally accessible information only
- Keep source links
- Summarize instead of copying
- Add confidence levels
- Add risk notes
- Add standardized risk levels
- Use human review before publishing or monetizing reports
- Avoid guaranteed income or guaranteed sales claims
- Respect platform rules and third-party licenses
TrendPilot AI workflows should not:
- Scrape private personal data
- Build contact databases
- Send spam
- Generate fake reviews
- Generate fake engagement
- Farm accounts
- Bypass platform restrictions
- Copy competitor images or creator content
- Repackage third-party code as original work
- Claim guaranteed product demand or profit
TrendPilot AI references external tools such as n8n, Firecrawl, Dify, Browser-use, and Google Sheets.
This repository does not:
- Copy third-party source code
- Redistribute third-party workflow exports
- Remove third-party attribution
- Repackage external tools as TrendPilot AI
- Claim official partnership with referenced projects
For external project references, see:
Before publishing, selling, or sending any report, confirm:
- Sources are public
- Source links are included
- Claims are supported by evidence
- No private personal data is included
- No long copyrighted text is copied
- No platform restriction bypass is involved
- No fake engagement or spam is involved
- No product success is guaranteed
- Confidence levels are included
- Risk notes are included
- Risk levels are included
- Human reviewer has approved the output
TrendPilot AI may support ethical monetization models such as:
- Paid trend reports
- Paid newsletters
- Research templates
- Product opportunity scorecards
- Internal dashboards
- Consulting reports
- Educational content
- Workflow setup services
It should not be marketed as:
- Guaranteed income system
- Auto-money bot
- Passive profit machine
- Platform loophole
- Spam automation system
- Scraping farm
See:
Core additions now included:
schemas/
├── trend-signal.schema.json
├── product-score.schema.json
└── report-record.schema.json
examples/
├── sample-daily-report-en.md
├── sample-daily-report-cn.md
├── sample-product-score.csv
├── sample-source-log.csv
└── python/
├── README.md
├── daily_report_generator.py
└── score_product_idea.py
SECURITY.md
.github/FUNDING.yml
Planned next additions:
.github/
└── ISSUE_TEMPLATE/
Other planned files:
CONTRIBUTING.md
CODE_OF_CONDUCT.md
TrendPilot AI is for research and educational purposes only.
It does not guarantee:
- Product demand
- Sales
- Profit
- Business success
- Viral content
- Marketplace ranking
- Advertising performance
- Subscriber growth
- Any financial outcome
Users should verify all sources, review platform rules, check compliance requirements, and conduct their own due diligence before making business decisions.
Read the full disclaimer:
This repository uses the MIT License for original TrendPilot AI content.
This does not change the licenses of third-party tools referenced in this repository.
Before using any external project, review that project's own license, documentation, and terms.
- Sample Product Score JSON
- Sample Trend Signal JSON
- Sample Report Record JSON
- Sample Product Score Input JSON
If TrendPilot AI helps you save time or gives you value, you can support the project here:
- ⭐ Star this repository
- 💰 Support via PayPal: https://www.paypal.me/lamguo
Thank you for supporting open-source development.
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