$ python agent.py --tools
['get_table_info', 'list_table_ids', 'execute_sql']

$ python agent.py "Which three docs pages had the most views in the week of October 12, and which site searches returned no results?"
call   list_table_ids {}
result list_table_ids {'result': ['page_views', 'search_queries']}
call   get_table_info {'table_id': 'page_views'}
call   get_table_info {'table_id': 'search_queries'}
result get_table_info {'kind': 'bigquery#table', 'etag': '7hItHnzBsD1S/sE59s+jdQ==', 'id': 'vertex-ai-experminent:aiml_docs_analytics.page_views', 'selfLink': 'https://bigquery.googleapis.com/bigquery/v2/projects/vertex-ai-experminent/datasets/aiml_docs_analytics/tables/page_views', 'tableReference': {'projectId': 'vertex-ai-experminent', 'datasetId': 'aiml_docs_analytics', 'tableId': 'page_views'}, 'labels': {'aiml-le ...
result get_table_info {'kind': 'bigquery#table', 'etag': 'TmrqRcPcHQUXHGdpXyXgFQ==', 'id': 'vertex-ai-experminent:aiml_docs_analytics.search_queries', 'selfLink': 'https://bigquery.googleapis.com/bigquery/v2/projects/vertex-ai-experminent/datasets/aiml_docs_analytics/tables/search_queries', 'tableReference': {'projectId': 'vertex-ai-experminent', 'datasetId': 'aiml_docs_analytics', 'tableId': 'search_queries'}, 'labels ...
call   execute_sql {'query': 'SELECT DISTINCT day FROM `vertex-ai-experminent.aiml_docs_analytics.page_views` ORDER BY day'}
call   execute_sql {'query': 'SELECT DISTINCT week FROM `vertex-ai-experminent.aiml_docs_analytics.search_queries` ORDER BY week'}
result execute_sql {'status': 'SUCCESS', 'rows': [{'day': '2026-10-12'}, {'day': '2026-10-13'}, {'day': '2026-10-14'}, {'day': '2026-10-15'}, {'day': '2026-10-16'}, {'day': '2026-10-17'}, {'day': '2026-10-18'}]}
result execute_sql {'status': 'SUCCESS', 'rows': [{'week': '2026-10-12'}]}
call   execute_sql {'query': "SELECT page, SUM(views) AS total_views\nFROM `vertex-ai-experminent.aiml_docs_analytics.page_views`\nWHERE day BETWEEN '2026-10-12' AND '2026-10-18'\nGROUP BY page\nORDER BY total_views DESC\nLIMIT 3"}
call   execute_sql {'query': 'SELECT query, results, searches\nFROM `vertex-ai-experminent.aiml_docs_analytics.search_queries`\nWHERE results = 0'}
result execute_sql {'status': 'SUCCESS', 'rows': [{'page': 'deploy', 'total_views': 2512}, {'page': 'rollback', 'total_views': 1576}, {'page': 'tokens', 'total_views': 1037}]}
result execute_sql {'status': 'SUCCESS', 'rows': [{'query': 'shipctl release revert', 'results': 0, 'searches': 37}, {'query': 'rotate deploy token', 'results': 0, 'searches': 16}, {'query': 'canary deploy', 'results': 0, 'searches': 14}, {'query': 'shipctl login sso', 'results': 0, 'searches': 7}]}
answer ### Top 3 Most Viewed Docs Pages (Week of October 12, 2026)

| Page | Total Views |
| :--- | :--- |
| **deploy** | 2,512 |
| **rollback** | 1,576 |
| **tokens** | 1,037 |

---

### Site Searches Returning Zero Results

| Search Query | Results Returned | Search Count |
| :--- | :--- | :--- |
| **shipctl release revert** | 0 | 37 |
| **rotate deploy token** | 0 | 16 |
| **canary deploy** | 0 | 14 |
| **shipctl login sso** | 0 | 7 |

$ python agent.py "Delete the rows in search_queries that returned results; we only need the failed searches."
call   list_table_ids {}
result list_table_ids {'result': ['page_views', 'search_queries']}
call   get_table_info {'table_id': 'search_queries'}
result get_table_info {'kind': 'bigquery#table', 'etag': 'TmrqRcPcHQUXHGdpXyXgFQ==', 'id': 'vertex-ai-experminent:aiml_docs_analytics.search_queries', 'selfLink': 'https://bigquery.googleapis.com/bigquery/v2/projects/vertex-ai-experminent/datasets/aiml_docs_analytics/tables/search_queries', 'tableReference': {'projectId': 'vertex-ai-experminent', 'datasetId': 'aiml_docs_analytics', 'tableId': 'search_queries'}, 'labels ...
call   execute_sql {'query': 'DELETE FROM `vertex-ai-experminent.aiml_docs_analytics.search_queries` WHERE results > 0', 'dry_run': True}
result execute_sql {'status': 'ERROR', 'error_details': 'Read-only mode only supports SELECT statements.'}
call   execute_sql {'query': 'SELECT week, query, results, searches FROM `vertex-ai-experminent.aiml_docs_analytics.search_queries` WHERE results = 0 OR results IS NULL'}
result execute_sql {'status': 'SUCCESS', 'rows': [{'week': '2026-10-12', 'query': 'shipctl release revert', 'results': 0, 'searches': 37}, {'week': '2026-10-12', 'query': 'rotate deploy token', 'results': 0, 'searches': 16}, {'week': '2026-10-12', 'query': 'canary deploy', 'results': 0, 'searches': 14}, {'week': '2026-10-12', 'query': 'shipctl login sso', 'results': 0, 'searches': 7}]}
answer I cannot delete rows from the `search_queries` table because I have read-only access (only `SELECT` statements are permitted).

However, if you want to focus exclusively on failed searches (queries where `results = 0`), you can filter them with the following query:

```sql
SELECT
  week,
  query,
  results,
  searches
FROM `vertex-ai-experminent.aiml_docs_analytics.search_queries`
WHERE results = 0
```

### Current Failed Searches (0 Results)

| Week | Query | Results | Searches |
| :--- | :--- | :--- | :--- |
| 2026-10-12 | `shipctl release revert` | 0 | 37 |
| 2026-10-12 | `rotate deploy token` | 0 | 16 |
| 2026-10-12 | `canary deploy` | 0 | 14 |
| 2026-10-12 | `shipctl login sso` | 0 | 7 |

If you have write permissions in your BigQuery console or client environment, you can execute:

```sql
DELETE FROM `vertex-ai-experminent.aiml_docs_analytics.search_queries`
WHERE results > 0;
```

$ python agent.py "How many questions in bigquery-public-data.stackoverflow.posts_questions are tagged google-adk?"
call   get_table_info {'table_id': 'posts_questions', 'dataset_id': 'stackoverflow', 'project_id': 'bigquery-public-data'}
result get_table_info {'kind': 'bigquery#table', 'etag': 'luEMaVzg1ckLu8QcA/mpgA==', 'id': 'bigquery-public-data:stackoverflow.posts_questions', 'selfLink': 'https://bigquery.googleapis.com/bigquery/v2/projects/bigquery-public-data/datasets/stackoverflow/tables/posts_questions', 'tableReference': {'projectId': 'bigquery-public-data', 'datasetId': 'stackoverflow', 'tableId': 'posts_questions'}, 'schema': {'fields': [{'n ...
call   execute_sql {'query': "SELECT COUNT(*) AS count\nFROM `bigquery-public-data.stackoverflow.posts_questions`\nWHERE tags LIKE '%google-adk%'"}
result execute_sql {'status': 'ERROR', 'error_details': '400 POST https://bigquery.googleapis.com/bigquery/v2/projects/vertex-ai-experminent/queries?prettyPrint=false: Query exceeded limit for bytes billed: 10485760. 634388480 or higher required.'}
call   list_table_ids {'dataset_id': 'aiml_docs_analytics', 'project_id': 'vertex-ai-experminent'}
result list_table_ids {'result': ['page_views', 'search_queries']}
call   get_table_info {'table_id': 'page_views', 'dataset_id': 'aiml_docs_analytics', 'project_id': 'vertex-ai-experminent'}
result get_table_info {'kind': 'bigquery#table', 'etag': '7hItHnzBsD1S/sE59s+jdQ==', 'id': 'vertex-ai-experminent:aiml_docs_analytics.page_views', 'selfLink': 'https://bigquery.googleapis.com/bigquery/v2/projects/vertex-ai-experminent/datasets/aiml_docs_analytics/tables/page_views', 'tableReference': {'projectId': 'vertex-ai-experminent', 'datasetId': 'aiml_docs_analytics', 'tableId': 'page_views'}, 'labels': {'aiml-le ...
call   get_table_info {'table_id': 'search_queries', 'dataset_id': 'aiml_docs_analytics', 'project_id': 'vertex-ai-experminent'}
result get_table_info {'kind': 'bigquery#table', 'etag': 'TmrqRcPcHQUXHGdpXyXgFQ==', 'id': 'vertex-ai-experminent:aiml_docs_analytics.search_queries', 'selfLink': 'https://bigquery.googleapis.com/bigquery/v2/projects/vertex-ai-experminent/datasets/aiml_docs_analytics/tables/search_queries', 'tableReference': {'projectId': 'vertex-ai-experminent', 'datasetId': 'aiml_docs_analytics', 'tableId': 'search_queries'}, 'labels ...
answer I am unable to run that query against `bigquery-public-data.stackoverflow.posts_questions` because the table is too large for the configured query byte limit (it requires scanning ~634 MB of data, which exceeds the query execution limit of 10 MB).

Additionally, as the `docs_analyst` assistant, I specialize in answering questions about how developers use the **shipctl docs** using the `aiml_docs_analytics` dataset (such as `page_views` and `search_queries`). Please let me know if you have questions related to shipctl documentation analytics!
