---
pretty_name: OpenToolTrace-X (Platinum)
language:
- en
license: apache-2.0
task_categories:
- text-generation
- question-answering
- reinforcement-learning
tags:
- agents
- tool-use
- trajectories
- verification
- code
- bash
- git
size_categories:
- n<1K  # sample pack; replace after scaling
dataset_info:
  creator: "Within US AI"
  contact: "Within US AI"
  created: "2025-12-30T16:53:41Z"
  schema: "See Features section below"
---

# OpenToolTrace-X (Platinum)

**Developer/Publisher:** Within US AI  
**Version:** 0.1.0 (sample pack)  
**Created:** 2025-12-30T16:53:41Z

## What this dataset is
`OpenToolTrace-X` is a **replayable, verifiable** corpus of tool-using agent trajectories.

Each record contains:
- A user goal (`prompt`) and constraints
- An `initial_state` describing the starting environment/repo snapshot
- A `trajectory` (tool calls + observations)
- A `final_state` (artifacts/diff/output)
- `verification` (tests, checksums, exit codes) to make outcomes **machine-checkable**

## Features / schema (JSONL)
- `task_id` (string)
- `domain` (string; e.g., `python`, `bash`, `git`, `data`)
- `difficulty` (int; 1–5)
- `prompt` (string)
- `constraints` (string)
- `initial_state` (object)
- `trajectory` (list of objects)
- `final_state` (object)
- `verification` (object)
- `tags` (list of strings)
- `created_utc` (string; ISO 8601)
- `license_note` (string)

### Trajectory step format
Each step is a dict:
- `tool` (e.g., `bash`, `python`, `git`)
- `action` (command / code / args)
- `observation` (stdout / structured output)
- `exit_code` (int)
- `stderr` (string, optional)
- `artifacts_written` (list of strings, optional)

## Data splits
- `data/train.jsonl`
- `data/validation.jsonl`
- `data/test.jsonl`

## Replay harness (scaffold)
See `replay_harness/` for a safe, non-executing replay viewer.
Integrate your own sandbox executor for real replays.

## How to load
```python
from datasets import load_dataset
ds = load_dataset("json", data_files={
    "train": "data/train.jsonl",
    "validation": "data/validation.jsonl",
    "test": "data/test.jsonl",
})
print(ds["train"][0])
```