Vigneshwaran/dataclaw-peteromallet
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 is yours to share. Exported with DataClaw. Tag: dataclaw — Browse all DataClaw datasets Stats Metric Value Sessions… See the full description on the dataset page: https://huggingface.co/datasets/Vigneshwaran/dataclaw-peteromallet.
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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 is yours to share.
Exported with DataClaw.
Tag: `dataclaw` — Browse all DataClaw datasets
Stats
Models
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/dataclaw-peteromallet", split="train")Export your own
pip install dataclaw
dataclaw