---
license: mit
task_categories:
- tabular-classification
- reinforcement-learning
tags:
- finance
- trading
- nifty
- algorithmic-trading
- ai-agent
- session-logs
pretty_name: Nifty AI Agent Session Logs & Accuracy Telemetry
size_categories:
- n<1K
---

# 🚀 Nifty 50 AI Agent — Kaggle Session Logs & Accuracy Telemetry

This dataset repository contains structured session telemetry, real-time trade signals,
risk gate evaluations, agent decisions, and accuracy improvement reports generated by
the **Nifty AI Brain Agent** running autonomously on Kaggle dual T4 GPU environment.

---

## 📂 Repository Structure

```
nagarhimanshu37/nifty-session-logs
├── README.md                      ← Telemetry overview & session log index
├── latest_report.json             ← Latest session accuracy & weakness report
└── sessions/
    └── <session_id>/
        ├── session_meta.jsonl     ← Session start/end timestamps & runtime metadata
        ├── session_summary_raw.json ← Quick session totals
        ├── accuracy_report.json   ← Computed accuracy, win rates & weakness analysis
        ├── improvement_notes.md   ← Human-readable action items for next prompt/code edit
        ├── signals.jsonl          ← Every generated AlphaSignal before risk gate
        ├── trades.jsonl           ← Every approved trade + execution/outcome
        ├── vetoed_trades.jsonl    ← Every trade rejected by QuantitativeRiskAgent
        ├── agent_decisions.jsonl  ← Sub-agent cycle steps and market scans
        ├── heartbeats.jsonl       ← 24/7 supervisor health snapshots
        └── errors.jsonl           ← Anomaly reports & runtime exceptions
```

---

## 🎯 Purpose

1. **Continuous Learning**: Track which setups (CPR Breakout, VWAP Rejection, Trap Hunter) perform best.
2. **Defect & Weakness Isolation**: Automatically identify why signals fail (e.g. low VIX chop, opening 15-min noise, wrong delta).
3. **Agent Tuning**: Use `improvement_notes.md` to refine strategy thresholds, risk weights, and LLM reasoning prompts.

---

*Automatically synced from Kaggle dual T4 runners via `HFSessionPusher`.*