Update README.md

README.md

@@ -1,3 +1,69 @@
 ---
 license: apache-2.0
+task_categories:
+- text-generation
+language:
+- en
+tags:
+- tool_calling
+- Qwen3_4B
+size_categories:
+- 1K<n<10K
 ---
+
+# Financial Fundamentals Tool-Calling Dataset
+
+This dataset contains synthetic examples for training and evaluating financial tool-calling models. Each example pairs a natural-language user request about company fundamentals with a structured JSON function call.
+
+The dataset is designed for models that should translate financial requests into tool calls instead of answering directly.
+
+## Task
+
+Given a user query such as:
+
+```text
+Retrieve net income and diluted shares for Broadcom from 2006 to 2018.
+```
+The model should produce a JSON call like:
+
+```
+{
+  "action": "call",
+  "function": "get_fundamentals",
+  "arguments": {
+    "queries": [
+      {
+        "symbols": ["Broadcom"],
+        "metrics": ["Net Income", "Diluted Shares"],
+        "start_year": 2006,
+        "end_year": 2018
+      }
+    ]
+  }
+}
+```
+
+## Dataset Fields
+
+The dataset includes fields such as:
+
+- `query`: The natural-language financial request.
+- `completion`: The target JSON tool call.
+- `text`: Chat-formatted training text.
+- `messages`: Chat-style system, user, and assistant messages.
+- `metadata`: Generation metadata, including companies, metrics, years, and grouping information.
+- `source_index`: Index of the original source example.
+
+## Use Cases
+
+This dataset can be used to train or evaluate models for:
+
+- Financial function calling
+- Structured JSON generation
+- Tool routing for agentic finance systems
+- Fundamentals retrieval request parsing
+- Company-metric-year extraction
+
+## Limitations
+
+The dataset is synthetic and focused on financial fundamentals requests. It does not contain live financial values, investment advice, or real-time market data. Models trained on this dataset should have their JSON outputs validated before any downstream tool execution.