Improve dataset card with metadata, description, and sample usage

This PR improves the dataset card by adding YAML metadata (license and task category) and structured markdown content that describes the PageGuide datasets with their respective usage examples found in the GitHub repository.

README.md

@@ -1,5 +1,52 @@
-Link to the project: https://pageguide.github.io/
+---
+task_categories:
+- other
+license: mit
+---
 
-Link to the paper: https://huggingface.co/papers/2604.23772
+# PageGuide Dataset
 
-Link to the code: https://github.com/tin-xai/pageguide
+This repository contains dataset artifacts from the paper [PageGuide: Browser extension to assist users in navigating a webpage and locating information](https://huggingface.co/papers/2604.23772).
+
+* **Project Page:** https://pageguide.github.io/
+* **Repository:** https://github.com/tin-xai/pageguide
+* **Paper:** [Hugging Face Paper Page](https://huggingface.co/papers/2604.23772)
+
+---
+
+## Dataset Description
+
+PageGuide was evaluated in a controlled within-subjects user study. The evaluation data is structured into four datasets:
+
+### 1. `pageguide_userstudy`
+* **Purpose:** Raw interaction logs from the user study — completion times, chat transcripts, correctness labels, paired statistical results, and post-study survey responses.
+* **Sample Usage:**
+```python
+from datasets import load_dataset
+tasks  = load_dataset("ttn0011/pageguide_userstudy", data_files="tasks.csv", split="train").to_pandas()
+paired = load_dataset("ttn0011/pageguide_userstudy", data_files="paired_times.csv", split="train").to_pandas()
+```
+
+### 2. `pageguide_find_data`
+* **Purpose:** Task stimuli for the **Find** condition — 10 real webpages (NASA, Wikipedia, Cleveland Clinic, WWF, Britannica, JMLR) each annotated with up to 2 factual questions, ground-truth answers, and supporting evidence spans.
+* **Sample Usage:**
+```python
+from datasets import load_dataset
+find_tasks = load_dataset("ttn0011/pageguide_find_data", split="train").to_pandas()
+```
+
+### 3. `pageguide_guide_data`
+* **Purpose:** Task stimuli for the **Guide** condition — 7 procedural tasks across 6 platforms (Google Sheets, Google Docs, Google Slides, Coda, TradingView, Scratch), labelled Easy or Medium difficulty.
+* **Sample Usage:**
+```python
+from datasets import load_dataset
+guide_tasks = load_dataset("ttn0011/pageguide_guide_data", split="train").to_pandas()
+```
+
+### 4. `pageguide_hide_data`
+* **Purpose:** Task stimuli for the **Hide** condition — 37 annotated webpage snapshots (Amazon, Netflix, TechCrunch, Allrecipes, Spotify, Yelp, and more) with `(user_goal, hide_query, difficulty, hidden_elements)` annotations and ground-truth CSS selectors.
+* **Sample Usage:**
+```python
+from datasets import load_dataset
+hide_tasks = load_dataset("ttn0011/pageguide_hide_data", split="train").to_pandas()
+```