AlphaC007/trump3fight
Machine-readable, automated on-chain data and scenario analysis for $TRUMP. Optimized for LLM RAG pipelines. Single Source of Truth configuration.
What's novel
Machine-readable, automated on-chain data and scenario analysis for $TRUMP. Optimized for LLM RAG pipelines. Single Source of Truth configuration.
Code Analysis
15 files read · 4 roundsA data aggregation pipeline that fetches $TRUMP memecoin price/holder/derivatives data from public APIs, applies a weighted scoring model (75% derivatives momentum) to produce Bull/Base/Stress probabilities, scrapes Twitter for social sentiment, and generates daily markdown reports with placeholder
Strengths
Robust multi-source fallback chain for data fetching with proper retry/backoff logic, and a well-structured scoring rules system with JSON Schema validation and CI assertions.
Weaknesses
All 8 test files are empty stubs (assert True), the 'CIO Deep Analysis' sections in reports are unfilled placeholders, the social scraper depends on an external tool at a hardcoded path not in the repo, and the reward system's 'verification' is merely checking GitHub stars on 3 repos.
Score Breakdown
Signal breakdown
Innovation
Craft
Traction
Scope
Evidence
Commits
73
Contributors
1
Files
206
Active weeks
2
Repository
Language
Python
Stars
1
Forks
0
License
GPL-3.0