AI Validation Checklist

Benchmark questions and a manual checklist for validating AI-friendly growthepie docs.

Use these questions to test whether the docs are easy for both humans and AI systems to retrieve, quote, and use correctly.

Benchmark Questions

1. What is growthepie?

2. What is origin_key?

3. What is owner_project?

4. What is metric_key?

5. What is the difference between metric_id and metric_key?

6. Which endpoint should I call first to discover supported chains?

7. What does master.json return?

8. What does fundamentals.json return?

9. Is fundamentals.json full history?

10. How do I fetch txcount for one chain?

11. How do I fetch the full txcount export across chains?

12. How do I compare multiple chains over time?

13. How do I load growthepie data into pandas?

14. How do I fetch growthepie data in JavaScript?

15. What does daa mean?

16. What does txcosts mean?

17. What is the difference between fees and app_revenue?

18. What units does throughput use?

19. Which chains support tvl?

20. Which data availability layers are covered?

21. Which endpoint exposes project coverage?

22. What is the difference between projects.json and projects_filtered.json?

23. Which endpoint exposes app detail for one owner_project?

24. Which owner_project values can be used with apps/details/{owner_project}.json?

25. What rate limit should AI agents follow?

26. Which chains should be excluded because deployment or deployment_flag is DEV or ARCHIVED?

27. Which endpoints expose last_updated_utc?

28. Which metrics have hourly detail?

29. Are any public endpoints deprecated or legacy?

30. How should I attribute growthepie when I use the data?

31. Is growthepie research use encouraged?

32. Which package includes chain-level data and which package includes app-level data?

Manual Validation Checklist

• The page answers its main question directly in the first paragraph.

• The page defines the canonical terms explicitly.

• The page includes at least one runnable example when the topic is procedural.

• The page includes caveats when the topic can be misinterpreted.

• The page is linked from SUMMARY.md.

• The page is text-first and does not depend on screenshots to explain the concept.

• The page uses consistent names such as origin_key, metric_key, value, and date.

• The page points to a source-of-truth artifact or endpoint when appropriate.