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README.md

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+---
+license: mit
+language:
+- en
+tags:
+- agentic-scenarios
+- synthetic-data
+- prompt-dataset
+- hermes
+size_categories:
+- 100<n<1K
+---
+
+# Talos Scenarios
+
+A collection of **602 unique agentic task scenarios/prompts** extracted from the Talos synthetic trace generation pipeline. These scenarios were used to generate the `DJLougen/Talos-kimi-k2.6-Hermes-synthetic` dataset via kimi-k2.6.
+
+## Source Dataset
+
+These scenarios originate from: **DJLougen/Talos-kimi-k2.6-Hermes-synthetic**
+
+## What's Inside
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `scenario` | str | The user prompt / task description |
+| `category` | str | Domain tag: `coding`, `reasoning`, `creative`, `tool_use`, `science`, `history`, `business`, `philosophy`, `general` |
+| `complexity` | str | `low` / `medium` / `high` based on word count |
+| `requires_tools` | bool | Whether the scenario likely requires external tool/API access |
+| `word_count` | int | Length of the prompt in words |
+| `source` | str | Parent dataset reference |
+
+## Statistics
+
+| Category | Count |
+|----------|-------|
+| general | 160 |
+| coding | 115 |
+| history | 115 |
+| science | 83 |
+| tool_use | 54 |
+| creative | 53 |
+| reasoning | 16 |
+| philosophy | 4 |
+| business | 2 |
+
+**Total:** 602 unique scenarios
+
+## Usage
+
+### Load with HuggingFace `datasets`
+
+```python
+from datasets import load_dataset
+ds = load_dataset("DJLougen/Talos-Scenarios", split="train")
+print(ds[0]["scenario"])
+```
+
+### Filter by category
+
+```python
+coding = ds.filter(lambda x: x["category"] == "coding")
+```
+
+### Use for synthetic trace generation
+
+```python
+for example in ds:
+    prompt = example["scenario"]
+    # Feed to your LLM to generate agentic traces
+```
+
+## License
+MIT — synthetic data generated for training purposes.
+
+## Contact
+Created by DJLougen as part of the Talos agentic trace curation pipeline.