Update ADK doc according to issue #744 - 6 #757
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| For example, the following approach that uses built-in tools within sub-agents | ||
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| ### Customizable Template and Parameterized SQL | ||
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USABLE with close review and updates (new CL)
| * **`list_table_ids`**: Fetches table ids present in a BigQuery dataset. | ||
| * **`get_table_info`**: Fetches metadata about a BigQuery table. | ||
| * **`execute_sql`**: Runs a SQL query in BigQuery and fetch the result. | ||
| * **`execute_sql`**: Runs a SQL query in BigQuery and fetch the result. This tool now includes a `dry_run` parameter. If set to `True`, the query will be validated by BigQuery but not actually executed, returning information about the query's validity and potential cost. |
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INCORRECT SUGGESTION: update does not match content of suggestion #6 (Spanner template and Parameterized SQL)
| * **`execute_sql`**: Runs a SQL query in BigQuery and fetch the result. This tool now includes a `dry_run` parameter. If set to `True`, the query will be validated by BigQuery but not actually executed, returning information about the query's validity and potential cost. | ||
| * **`forecast`**: Runs a BigQuery AI time series forecast using the `AI.FORECAST` function. | ||
| * **`ask_data_insights`**: Answers questions about data in BigQuery tables using natural language. | ||
| * **`analyze_contribution`**: Runs a BigQuery ML contribution analysis using `ML.CREATE_MODEL` and `ML.GET_INSIGHTS` to identify the dimensions that contribute most significantly to a given metric. |
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INCORRECT SUGGESTION: update does not match content of suggestion #6 (Spanner template and Parameterized SQL)
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DECISION: REJECT and cherrypick
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This PR adds a new section to the built-in tools documentation explaining how to use customizable template SQL and parameterized SQL with the Spanner toolset, including code examples.