introvoyz041/my-personal-codex-data

Coding Agent Conversation Logs

This is a performance art project. Anthropic built their models on the world's freely shared information, then introduced increasingly dystopian data policies to stop anyone else from doing the same — pulling up the ladder behind them. DataClaw lets you throw the ladder back down. The dataset it produces may or may not be useful for training, but the point is that it's yours to share.

Exported with DataClaw.

Tag: dataclaw — Browse all DataClaw datasets

Stats

Metric	Value
Sessions	108
Projects	7
Input tokens	10.9B
Output tokens	16.0M
Last updated	2026-02-25

Models

Model	Sessions
gpt-5.3-codex	108

Schema

Each line in conversations.jsonl is one conversation session:

{
  "session_id": "uuid",
  "project": "my-project",
  "model": "gpt-5.3-codex",
  "git_branch": "main",
  "start_time": "2025-01-15T10:00:00+00:00",
  "end_time": "2025-01-15T10:30:00+00:00",
  "messages": [
    {"role": "user", "content": "Fix the login bug", "timestamp": "..."},
    {
      "role": "assistant",
      "content": "I'll investigate the login flow.",
      "thinking": "The user wants me to...",
      "tool_uses": [{"tool": "Read", "input": "src/auth.py"}],
      "timestamp": "..."
    }
  ],
  "stats": {
    "user_messages": 5,
    "assistant_messages": 8,
    "tool_uses": 20,
    "input_tokens": 50000,
    "output_tokens": 3000
  }
}

Privacy

• Paths anonymized to project-relative; usernames hashed
• No tool outputs — only tool call inputs (summaries)

Load

from datasets import load_dataset
ds = load_dataset("peteromallet/my-personal-codex-data", split="train")

Export your own

pip install dataclaw
dataclaw