Publish ATRD 1M dataset: Parquet, README, MIT License and tags

LICENSE

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+MIT License
+
+Copyright (c) 2026 Lelonthecodeur
+
+Permission is hereby granted, free of charge, to any person
+obtaining a copy of this software and associated documentation
+files (the "Software"), to deal in the Software without
+restriction, including without limitation the rights to use,
+copy, modify, merge, publish, distribute, sublicense,
+and/or sell copies of the Software, and to permit persons
+to whom the Software is furnished to do so, subject to
+the following conditions:
+
+The above copyright notice and this permission notice shall
+be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE
+OR OTHER DEALINGS IN THE SOFTWARE.

README.md

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+---
+license: mit
+language:
+- en
+pretty_name: Agent Training Reasoning Dataset Dense
+task_categories:
+- text-generation
+size_categories:
+- 1M<n<10M
+tags:
+- agentic-ai
+- agent-training
+- reasoning
+- tool-use
+- synthetic-data
+- parquet
+- multi-step-planning
+- decision-making
+- data-analysis
+- code-generation
+- workflow-automation
+- problem-solving
+- verification
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/*.parquet
+---
+
+# Agent Training Reasoning Dataset Dense
+
+**A synthetic dataset for general-purpose agentic AI training.**
+
+Repository: `Lelonthecodeur/agent-training-reasoning-dataset-dense`
+
+## Overview
+
+Agent Training Reasoning Dataset Dense (ATRD) is a
+programmatically generated dataset designed to provide
+structured examples across multiple agentic task domains.
+
+It focuses on task understanding, planning, tool selection,
+verification, decision-making and structured responses.
+
+## Dataset statistics
+
+| Property | Value |
+|---|---|
+| Total examples | 1,000,000 |
+| Domains | 20 |
+| Difficulty levels | 4 |
+| Format | Apache Parquet |
+| Compression | Zstandard |
+| Parquet shards | 20 |
+| Generator version | 1.0.0 |
+| Random seed | 42 |
+| Language | English |
+| Data type | Synthetic |
+
+## Domain coverage
+
+- planning
+- coding
+- research
+- data_analysis
+- mathematics
+- tool_selection
+- verification
+- project_management
+- information_retrieval
+- problem_solving
+- communication
+- safety
+- decision_making
+- debugging
+- scheduling
+- file_management
+- summarization
+- critical_thinking
+- workflow_automation
+- ambiguity_resolution
+
+## Difficulty distribution
+
+- advanced: 250000
+- basic: 250000
+- expert: 250000
+- intermediate: 250000
+
+## Dataset schema
+
+Each example contains:
+
+| Field | Description |
+|---|---|
+| id | Unique example identifier |
+| messages | System, user and assistant messages |
+| domain | Task domain |
+| difficulty | Difficulty category |
+| available_tools | Tools available in the scenario |
+| synthetic | Whether the example is synthetic |
+| generator_version | Generator version |
+
+The assistant message contains a structured JSON object
+with a proposed plan, actions, simulated tool trace,
+final answer and verification metadata.
+
+## Loading the dataset
+
+Install the required libraries:
+
+```bash
+pip install datasets pyarrow
+```
+
+Load the dataset:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset(
+    "Lelonthecodeur/agent-training-reasoning-dataset-dense",
+    split="train"
+)
+
+print(dataset)
+print(dataset[0])
+```
+
+## Generation methodology
+
+Examples are generated programmatically from domain-specific
+templates and randomized variables.
+
+IDs are deterministic and unique within this generation run.
+
+The dataset is divided into Parquet shards and compressed
+using Zstandard.
+
+## Important limitations
+
+This is a synthetic baseline dataset.
+
+- Tool traces are simulated placeholders, not real tool executions.
+- Plans and responses are template-generated.
+- Examples have not been independently human-verified.
+- The dataset may contain repetitive patterns.
+- Difficulty labels are assigned by a deterministic cycle,
+  not by independent difficulty evaluation.
+- Mathematical examples are limited to simple arithmetic.
+
+Do not interpret the dataset as one million independently
+verified reasoning trajectories.
+
+Independent quality evaluation, deduplication, diversity
+testing and benchmark validation are recommended before
+production training.
+
+## Intended uses
+
+- Agentic AI research
+- Tool-selection experiments
+- Planning and workflow experiments
+- Synthetic data pipeline development
+- Dataset engineering experiments
+
+## License
+
+Released under the MIT License.
+
+See the LICENSE file for the complete license text.
+
+## Citation
+
+```bibtex
+@misc{lelon_agent_training_reasoning_dataset,
+  title={Agent Training Reasoning Dataset Dense},
+  author={Lelonthecodeur},
+  year={2026},
+  publisher={Hugging Face},
+  url={https://huggingface.co/datasets/Lelonthecodeur/agent-training-reasoning-dataset-dense}
+}
+```
+
+## Maintainer
+
+Lelonthecodeur
+
+Dataset version: 1.0.0

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manifest.json

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+{
+  "name": "Agent Training Reasoning Dataset Dense",
+  "repository": "Lelonthecodeur/agent-training-reasoning-dataset-dense",
+  "version": "1.0.0",
+  "examples": 1000000,
+  "domains": 20,
+  "domain_distribution": {
+    "planning": 50000,
+    "coding": 50000,
+    "research": 50000,
+    "data_analysis": 50000,
+    "mathematics": 50000,
+    "tool_selection": 50000,
+    "verification": 50000,
+    "project_management": 50000,
+    "information_retrieval": 50000,
+    "problem_solving": 50000,
+    "communication": 50000,
+    "safety": 50000,
+    "decision_making": 50000,
+    "debugging": 50000,
+    "scheduling": 50000,
+    "file_management": 50000,
+    "summarization": 50000,
+    "critical_thinking": 50000,
+    "workflow_automation": 50000,
+    "ambiguity_resolution": 50000
+  },
+  "difficulty_distribution": {
+    "basic": 250000,
+    "intermediate": 250000,
+    "advanced": 250000,
+    "expert": 250000
+  },
+  "format": "parquet",
+  "compression": "zstd",
+  "synthetic": true,
+  "generator_version": "1.0.0",
+  "generation_seed": 42,
+  "parquet_shards": 20,
+  "license": "MIT",
+  "visibility": "public"
+}