Tksrivastava/autonomous-metal — IdeaCred

Autonomous Metal is an autonomous AI workflow designed to mimic a quantitative commodity analyst, transforming market data and economic indicators into explainable forecasts and analyst-style insights for LME Aluminum price movements.

What's novel

Autonomous Metal is an autonomous AI workflow designed to mimic a quantitative commodity analyst, transforming market data and economic indicators into explainable forecasts and analyst-style insights for LME Aluminum price movements.

Code Analysis

10 files read · 4 rounds

An autonomous market analysis system that combines CNN-based time-series forecasting with SHAP explainability and LLM-powered narrative generation to produce institutional-style LME Aluminum analyst reports

Strengths

Substantive ML implementation with real CNN models, custom loss functions, and proper regularization. Clean architecture with clear separation between core logic, pipelines, and API. Production-ready with FastAPI service, artifact management, and comprehensive logging.

Weaknesses

No test files present (test_quality=0). Missing readable LangGraph workflow definition in core/graph.py. Heavily dependent on Kaggle dataset availability.

Score Breakdown

Innovation

6 (25%)

Craft

65 (35%)

Traction

6 (15%)

Scope

80 (25%)

Signal breakdown

Innovation

Not Fork+1

Code Novelty+1

Concept Novelty+2

Craft

Ci+5

Tests-1

Polish+0

Releases+0

Has License+5

Code Quality+22

Readme Quality+15

Recent Activity+7

Structure Quality+5

Commit Consistency+2

Has Dependency Mgmt+5

Traction

Forks+0

Stars+6

Hn Points+0

Watchers+0

Early Traction+0

Devto Reactions+0

Community Contribs+0

Scope

Commits+8

Languages+5

Subsystems+10

Bloat Penalty+0

Completeness+7

Contributors+5

Authored Files+12

Readme Code Match+3

Architecture Depth+5

Implementation Depth+8

Evidence

Commits

68

Contributors

1

Files

41

Active weeks

5

TestsCI/CDREADMELicenseContributing

Repository

Language

Python

Stars

1

Forks

0

License

MIT