Your First Elastic Agent
openai-chatgptlangchain-pythonchatgptgenaielasticsearchelasticopenaiAIchatlogvectordatabasePythonsearchgenaistacksupporting-blog-contentvectorelasticsearch-labslangchainyour-first-elastic-agentapplications
Export
Your First Elastic Agent
This notebook is the API-driven companion to the blog post, "Your First Elastic Agent: From a Single Query to an AI-Powered Chat."
Here, we'll perform every step from the article—creating a tool, building an agent, and having a conversation—using Python to interact directly with the Agent Builder APIs.
Prerequisites
To run this notebook, you will need:
- An active Elastic Cloud Serverless Project.
- You can sign up for a free trial at Elastic Cloud Trial Page
- Create an
Elasticsearchtype project
- The URLs for both Elasticsearch and Kibana
- How to get ES URL
- For kibana, replace
.es.in the url with.kb.in the ES URL
- An API Key with
writepermissions for Elasticsearch and Kibana (same API Key.
[ ]
Enter your Elasticsearch Endpoint URL: https://your-first-elastic-agent-a4dc2b.es.us-central1.gcp.elastic.cloud:443 Enter your Elasticsearch API Key: bmU3SGRKa0JJdGhRdS1VdGJ5STg6a0ViYkZKcXA5ekx6LWNEZkR2TGxvZw== Using connection details: Elasticsearch URL: https://your-first-elastic-agent-a4dc2b.es.us-central1.gcp.elastic.cloud:443 Kibana URL: https://your-first-elastic-agent-a4dc2b.kb.us-central1.gcp.elastic.cloud:443 ES_API_KEY: ***************************vZw==
Load Financial Data
This section will load synthetic financial data into your Elastic project for use demoing:
- Tool creation
- Agent creation
- Using the agent with the converse api
If you have previously loaded the data you can skip this part.
If you want to use other data, you will have to adjust the ES|QL queries to match the fields you have, as well as adjust the agent prompt and conversation questions to match your data
[ ]
Cloning into 'synthetic-financial-data'... remote: Enumerating objects: 368, done. remote: Counting objects: 100% (95/95), done. remote: Compressing objects: 100% (70/70), done. remote: Total 368 (delta 27), reused 72 (delta 20), pack-reused 273 (from 1) Receiving objects: 100% (368/368), 19.93 MiB | 13.48 MiB/s, done. Resolving deltas: 100% (199/199), done. /content/synthetic-financial-data
[ ]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 937.5/937.5 kB 25.9 MB/s eta 0:00:00 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2.0/2.0 MB 68.3 MB/s eta 0:00:00 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 65.1/65.1 kB 4.6 MB/s eta 0:00:00
[ ]
Polling endpoint... (Attempt #1) ✅ Endpoint is ready.
[ ]
============================================================ 🚀 FAST DATA LOADER - ALL INDICES ============================================================ Settings: 1000 batch, 24 workers, timestamps→now Time: 2025-09-23 04:29:02 ============================================================ /usr/local/lib/python3.12/dist-packages/elasticsearch/_sync/client/__init__.py:311: SecurityWarning: Connecting to 'https://your-first-elastic-agent-a4dc2b.es.us-central1.gcp.elastic.cloud:443' using TLS with verify_certs=False is insecure _transport = transport_class( Elasticsearch client initialized successfully. ✓ Connected to Elasticsearch 📁 Accounts: 7,000 documents 📁 Holdings: 122,923 documents 📁 Assets: 183 documents 📁 News: 550 documents 📁 Reports: 120 documents 📊 Total: 130,776 documents across 5 indices ============================================================ ⏳ Loading Accounts...Starting: financial_accounts (workers: 24, updating timestamps to current time) Starting: financial_accounts (workers: 24, updating timestamps to current time) Creating index 'financial_accounts'... ✓ Successfully created index 'financial_accounts' Updating timestamps to: 2025-09-23T04:29:03 [04:29:05] financial_accounts: batch 1/7 complete (1000 docs, 1000 total) [04:29:05] financial_accounts: batch 2/7 complete (1000 docs, 2000 total) [04:29:05] financial_accounts: batch 3/7 complete (1000 docs, 3000 total) [04:29:05] financial_accounts: batch 4/7 complete (1000 docs, 4000 total) [04:29:05] financial_accounts: batch 5/7 complete (1000 docs, 5000 total) [04:29:05] financial_accounts: batch 6/7 complete (1000 docs, 6000 total) [04:29:05] financial_accounts: batch 7/7 complete (1000 docs, 7000 total) ✓ 2.9s (2439 docs/sec) ⏳ Loading Holdings...Starting: financial_holdings (workers: 24, updating timestamps to current time) Starting: financial_holdings (workers: 24, updating timestamps to current time) Creating index 'financial_holdings'... ✓ Successfully created index 'financial_holdings' Updating timestamps to: 2025-09-23T04:29:06 [04:29:09] financial_holdings: batch 1/123 complete (1000 docs, 1000 total) [04:29:09] financial_holdings: batch 2/123 complete (1000 docs, 2000 total) [04:29:09] financial_holdings: batch 3/123 complete (1000 docs, 3000 total) [04:29:09] financial_holdings: batch 4/123 complete (1000 docs, 4000 total) [04:29:09] financial_holdings: batch 5/123 complete (1000 docs, 5000 total) [04:29:09] financial_holdings: batch 6/123 complete (1000 docs, 6000 total) [04:29:09] financial_holdings: batch 7/123 complete (1000 docs, 7000 total) [04:29:10] financial_holdings: batch 8/123 complete (1000 docs, 8000 total) [04:29:10] financial_holdings: batch 9/123 complete (1000 docs, 9000 total) [04:29:10] financial_holdings: batch 10/123 complete (1000 docs, 10000 total) [04:29:10] financial_holdings: batch 11/123 complete (1000 docs, 11000 total) [04:29:10] financial_holdings: batch 12/123 complete (1000 docs, 12000 total) [04:29:10] financial_holdings: batch 13/123 complete (1000 docs, 13000 total) [04:29:10] financial_holdings: batch 14/123 complete (1000 docs, 14000 total) [04:29:10] financial_holdings: batch 15/123 complete (1000 docs, 15000 total) [04:29:10] financial_holdings: batch 16/123 complete (1000 docs, 16000 total) [04:29:10] financial_holdings: batch 17/123 complete (1000 docs, 17000 total) [04:29:10] financial_holdings: batch 18/123 complete (1000 docs, 18000 total) [04:29:10] financial_holdings: batch 19/123 complete (1000 docs, 19000 total) [04:29:11] financial_holdings: batch 20/123 complete (1000 docs, 20000 total) [04:29:11] financial_holdings: batch 21/123 complete (1000 docs, 21000 total) [04:29:11] financial_holdings: batch 22/123 complete (1000 docs, 22000 total) [04:29:11] financial_holdings: batch 23/123 complete (1000 docs, 23000 total) [04:29:11] financial_holdings: batch 24/123 complete (1000 docs, 24000 total) [04:29:11] financial_holdings: batch 25/123 complete (1000 docs, 25000 total) [04:29:11] financial_holdings: batch 26/123 complete (1000 docs, 26000 total) [04:29:11] financial_holdings: batch 27/123 complete (1000 docs, 27000 total) [04:29:11] financial_holdings: batch 28/123 complete (1000 docs, 28000 total) [04:29:11] financial_holdings: batch 29/123 complete (1000 docs, 29000 total) [04:29:11] financial_holdings: batch 30/123 complete (1000 docs, 30000 total) [04:29:11] financial_holdings: batch 31/123 complete (1000 docs, 31000 total) [04:29:11] financial_holdings: batch 32/123 complete (1000 docs, 32000 total) [04:29:11] financial_holdings: batch 33/123 complete (1000 docs, 33000 total) [04:29:12] financial_holdings: batch 34/123 complete (1000 docs, 34000 total) [04:29:12] financial_holdings: batch 35/123 complete (1000 docs, 35000 total) [04:29:12] financial_holdings: batch 36/123 complete (1000 docs, 36000 total) [04:29:12] financial_holdings: batch 37/123 complete (1000 docs, 37000 total) [04:29:12] financial_holdings: batch 38/123 complete (1000 docs, 38000 total) [04:29:12] financial_holdings: batch 39/123 complete (1000 docs, 39000 total) [04:29:12] financial_holdings: batch 40/123 complete (1000 docs, 40000 total) [04:29:12] financial_holdings: batch 41/123 complete (1000 docs, 41000 total) [04:29:12] financial_holdings: batch 42/123 complete (1000 docs, 42000 total) [04:29:12] financial_holdings: batch 43/123 complete (1000 docs, 43000 total) [04:29:12] financial_holdings: batch 44/123 complete (1000 docs, 44000 total) [04:29:12] financial_holdings: batch 45/123 complete (1000 docs, 45000 total) [04:29:12] financial_holdings: batch 46/123 complete (1000 docs, 46000 total) [04:29:13] financial_holdings: batch 47/123 complete (1000 docs, 47000 total) [04:29:13] financial_holdings: batch 48/123 complete (1000 docs, 48000 total) [04:29:13] financial_holdings: batch 49/123 complete (1000 docs, 49000 total) [04:29:13] financial_holdings: batch 50/123 complete (1000 docs, 50000 total) [04:29:13] financial_holdings: batch 51/123 complete (1000 docs, 51000 total) [04:29:13] financial_holdings: batch 52/123 complete (1000 docs, 52000 total) [04:29:13] financial_holdings: batch 53/123 complete (1000 docs, 53000 total) [04:29:13] financial_holdings: batch 54/123 complete (1000 docs, 54000 total) [04:29:13] financial_holdings: batch 55/123 complete (1000 docs, 55000 total) [04:29:13] financial_holdings: batch 56/123 complete (1000 docs, 56000 total) [04:29:13] financial_holdings: batch 57/123 complete (1000 docs, 57000 total) [04:29:13] financial_holdings: batch 58/123 complete (1000 docs, 58000 total) [04:29:13] financial_holdings: batch 59/123 complete (1000 docs, 59000 total) [04:29:14] financial_holdings: batch 60/123 complete (1000 docs, 60000 total) [04:29:14] financial_holdings: batch 61/123 complete (1000 docs, 61000 total) [04:29:14] financial_holdings: batch 62/123 complete (1000 docs, 62000 total) [04:29:14] financial_holdings: batch 63/123 complete (1000 docs, 63000 total) [04:29:14] financial_holdings: batch 64/123 complete (1000 docs, 64000 total) [04:29:14] financial_holdings: batch 65/123 complete (1000 docs, 65000 total) [04:29:14] financial_holdings: batch 66/123 complete (1000 docs, 66000 total) [04:29:14] financial_holdings: batch 67/123 complete (1000 docs, 67000 total) [04:29:14] financial_holdings: batch 68/123 complete (1000 docs, 68000 total) [04:29:14] financial_holdings: batch 69/123 complete (1000 docs, 69000 total) [04:29:14] financial_holdings: batch 70/123 complete (1000 docs, 70000 total) [04:29:14] financial_holdings: batch 71/123 complete (1000 docs, 71000 total) [04:29:14] financial_holdings: batch 72/123 complete (1000 docs, 72000 total) [04:29:14] financial_holdings: batch 73/123 complete (1000 docs, 73000 total) [04:29:14] financial_holdings: batch 74/123 complete (1000 docs, 74000 total) [04:29:14] financial_holdings: batch 75/123 complete (1000 docs, 75000 total) [04:29:14] financial_holdings: batch 76/123 complete (1000 docs, 76000 total) [04:29:14] financial_holdings: batch 77/123 complete (1000 docs, 77000 total) [04:29:15] financial_holdings: batch 78/123 complete (1000 docs, 78000 total) [04:29:15] financial_holdings: batch 79/123 complete (1000 docs, 79000 total) [04:29:15] financial_holdings: batch 80/123 complete (1000 docs, 80000 total) [04:29:15] financial_holdings: batch 81/123 complete (1000 docs, 81000 total) [04:29:15] financial_holdings: batch 82/123 complete (1000 docs, 82000 total) [04:29:15] financial_holdings: batch 83/123 complete (1000 docs, 83000 total) [04:29:15] financial_holdings: batch 84/123 complete (1000 docs, 84000 total) [04:29:15] financial_holdings: batch 85/123 complete (1000 docs, 85000 total) [04:29:15] financial_holdings: batch 86/123 complete (1000 docs, 86000 total) [04:29:15] financial_holdings: batch 87/123 complete (1000 docs, 87000 total) [04:29:15] financial_holdings: batch 88/123 complete (1000 docs, 88000 total) [04:29:15] financial_holdings: batch 89/123 complete (1000 docs, 89000 total) [04:29:16] financial_holdings: batch 90/123 complete (1000 docs, 90000 total) [04:29:16] financial_holdings: batch 91/123 complete (1000 docs, 91000 total) [04:29:16] financial_holdings: batch 92/123 complete (1000 docs, 92000 total) [04:29:16] financial_holdings: batch 93/123 complete (1000 docs, 93000 total) [04:29:16] financial_holdings: batch 94/123 complete (1000 docs, 94000 total) [04:29:16] financial_holdings: batch 95/123 complete (1000 docs, 95000 total) [04:29:16] financial_holdings: batch 96/123 complete (1000 docs, 96000 total) [04:29:16] financial_holdings: batch 97/123 complete (1000 docs, 97000 total) [04:29:16] financial_holdings: batch 98/123 complete (1000 docs, 98000 total) [04:29:16] financial_holdings: batch 99/123 complete (1000 docs, 99000 total) [04:29:16] financial_holdings: batch 100/123 complete (1000 docs, 100000 total) [04:29:16] financial_holdings: batch 101/123 complete (1000 docs, 101000 total) [04:29:16] financial_holdings: batch 102/123 complete (1000 docs, 102000 total) [04:29:16] financial_holdings: batch 103/123 complete (1000 docs, 103000 total) [04:29:16] financial_holdings: batch 104/123 complete (1000 docs, 104000 total) [04:29:16] financial_holdings: batch 105/123 complete (1000 docs, 105000 total) [04:29:16] financial_holdings: batch 106/123 complete (1000 docs, 106000 total) [04:29:16] financial_holdings: batch 107/123 complete (1000 docs, 107000 total) [04:29:17] financial_holdings: batch 108/123 complete (1000 docs, 108000 total) [04:29:17] financial_holdings: batch 109/123 complete (1000 docs, 109000 total) [04:29:17] financial_holdings: batch 110/123 complete (1000 docs, 110000 total) [04:29:17] financial_holdings: batch 111/123 complete (1000 docs, 111000 total) [04:29:17] financial_holdings: batch 112/123 complete (1000 docs, 112000 total) [04:29:17] financial_holdings: batch 113/123 complete (1000 docs, 113000 total) [04:29:17] financial_holdings: batch 114/123 complete (1000 docs, 114000 total) [04:29:17] financial_holdings: batch 115/123 complete (1000 docs, 115000 total) [04:29:17] financial_holdings: batch 116/123 complete (1000 docs, 116000 total) [04:29:17] financial_holdings: batch 117/123 complete (1000 docs, 117000 total) [04:29:17] financial_holdings: batch 118/123 complete (1000 docs, 118000 total) [04:29:17] financial_holdings: batch 119/123 complete (1000 docs, 119000 total) [04:29:17] financial_holdings: batch 120/123 complete (1000 docs, 120000 total) [04:29:17] financial_holdings: batch 121/123 complete (923 docs, 120923 total) [04:29:17] financial_holdings: batch 122/123 complete (1000 docs, 121923 total) [04:29:17] financial_holdings: batch 123/123 complete (1000 docs, 122923 total) ✓ 12.4s (9899 docs/sec) ⏳ Loading Assets...Starting: financial_asset_details (workers: 24, updating timestamps to current time) Starting: financial_asset_details (workers: 24, updating timestamps to current time) Creating index 'financial_asset_details'... ✓ Successfully created index 'financial_asset_details' Updating timestamps to: 2025-09-23T04:29:18 [04:29:28] financial_asset_details: batch 1/1 complete (183 docs, 183 total) ✓ 10.6s (17 docs/sec) ⏳ Loading News...Starting: financial_news (workers: 24, updating timestamps to current time) Starting: financial_news (workers: 24, updating timestamps to current time) Creating index 'financial_news'... ✓ Successfully created index 'financial_news' Updating timestamps to: 2025-09-23T04:29:29 [04:30:30] financial_news: batch 1/1 FAILED ✓ 61.6s (9 docs/sec) ⏳ Loading Reports...Starting: financial_reports (workers: 24, updating timestamps to current time) Starting: financial_reports (workers: 24, updating timestamps to current time) Creating index 'financial_reports'... ✓ Successfully created index 'financial_reports' Updating timestamps to: 2025-09-23T04:30:31 [04:31:31] financial_reports: batch 1/1 FAILED ✓ 61.6s (2 docs/sec) ============================================================ ✅ COMPLETE: 5/5 indices loaded ⏱️ Total time: 149.1 seconds 📈 Average: 877 docs/second 🕐 Finished: 04:31:31 ============================================================
[ ]
🚀 Running in non-interactive mode... 🔍 Connecting to Elasticsearch... /usr/local/lib/python3.12/dist-packages/elasticsearch/_sync/client/__init__.py:311: SecurityWarning: Connecting to 'https://your-first-elastic-agent-a4dc2b.es.us-central1.gcp.elastic.cloud:443' using TLS with verify_certs=False is insecure _transport = transport_class( Elasticsearch client initialized successfully. ✅ Connected to Elasticsearch 8.11.0 📊 Index Status Summary ┏━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓ ┃ Index Name ┃ Exi… ┃ Docum… ┃ Size ┃ Errors ┃ ┡━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩ │ financial_asset_deta… │ ✓ │ 183 │ N/A │ │ │ financial_accounts │ ✓ │ 7,000 │ N/A │ │ │ financial_holdings │ ✓ │ 122,9… │ N/A │ │ │ financial_news │ ✓ │ 550 │ N/A │ │ │ financial_reports │ ✓ │ 120 │ N/A │ │ └───────────────────────┴──────┴────────┴────────┴─────────────────────────────┘ ✓ All 5 indices are properly configured Total: 130,776 documents (size not available in serverless)
Kibana Setup for Agent Builder
[ ]
✅ Successfully connected to Kibana! Cluster Name: kb Version: 9.2.0
#ONLY BEFORE PUBLIC PREVIEW: You will need to enable Agent Builder in your project.
Do to this
- Navigate to
Developer Toolsin Kibana - Run the following command
POST kbn://internal/kibana/settings { "changes": { "agentBuilder:enabled": true } } - Refresh your browser
You should now see Agents in the navigation side bar
Section 1: The Logic - Testing the ES|QL Query
Before we register our logic as a persistent Tool, it's a best practice to test the raw ES|QL query first. This allows us to validate the syntax and confirm it returns the data we expect. We'll use the /_query endpoint for this.
[ ]
✅ ES|QL query string is defined.
[ ]
✅ Request body is defined with test parameters:
{
"query": "\nFROM financial_news, financial_reports METADATA _index\n | WHERE sentiment == \"negative\"\n | WHERE coalesce(published_date, report_date) >= NOW() - TO_TIMEDURATION(?time_duration)\n | RENAME primary_symbol AS symbol\n | LOOKUP JOIN financial_asset_details ON symbol\n | LOOKUP JOIN financial_holdings ON symbol\n | LOOKUP JOIN financial_accounts ON account_id\n | WHERE account_holder_name IS NOT NULL\n | EVAL position_current_value = quantity * current_price.price\n | RENAME title AS news_title\n | KEEP\n account_holder_name, symbol, asset_name, news_title,\n sentiment, position_current_value, quantity, current_price.price,\n published_date, report_date\n | SORT position_current_value DESC\n | LIMIT 50\n",
"params": [
{
"time_duration": "2000 hours"
}
]
}
[ ]
Section 2: The Skill - Creating the Custom Tool
Now that we've validated our query, it's time to register it as a persistent Tool. This makes our logic available to any AI agent.
The most important parts of this definition are the description fields. The main description tells the agent what the tool does, and the parameter descriptions explain what kind of information the tool needs to run. The LLM uses this text to decide when and how to use our tool.
[ ]
✅ Tool definition for 'find_client_exposure_to_negative_news' is ready.
{
"id": "find_client_exposure_to_negative_news",
"tags": [
"retrieval",
"risk-analysis"
],
"type": "esql",
"description": "Finds client portfolio exposure to negative news. This tool scans recent news and reports for negative sentiment, identifies the associated asset, and finds all clients holding that asset. It returns a list sorted by the current market value of the position to highlight the highest potential risk.",
"configuration": {
"query": "\n FROM financial_news, financial_reports METADATA _index\n | WHERE sentiment == \"negative\"\n | WHERE coalesce(published_date, report_date) >= NOW() - TO_TIMEDURATION(?time_duration)\n | RENAME primary_symbol AS symbol\n | LOOKUP JOIN financial_asset_details ON symbol\n | LOOKUP JOIN financial_holdings ON symbol\n | LOOKUP JOIN financial_accounts ON account_id\n | WHERE account_holder_name IS NOT NULL\n | EVAL position_current_value = quantity * current_price.price\n | RENAME title AS news_title\n | KEEP\n account_holder_name, symbol, asset_name, news_title,\n sentiment, position_current_value, quantity, current_price.price,\n published_date, report_date\n | SORT position_current_value DESC\n | LIMIT 50\n ",
"params": {
"time_duration": {
"type": "keyword",
"description": "The timeframe to search back for negative news. Format is \"X hours\" DEFAULT TO 8760 hours "
}
}
}
} [ ]
Create Tool: find_client_exposure_to_negative_news
✅ Successfully created the tool!
{
"id": "find_client_exposure_to_negative_news",
"tags": [
"retrieval",
"risk-analysis"
],
"type": "esql",
"schema": {
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"time_duration"
],
"properties": {
"time_duration": {
"type": "string",
"description": "The timeframe to search back for negative news. Format is \"X hours\" DEFAULT TO 8760 hours "
}
},
"description": "Parameters needed to execute the query",
"additionalProperties": false
},
"readonly": false,
"description": "Finds client portfolio exposure to negative news. This tool scans recent news and reports for negative sentiment, identifies the associated asset, and finds all clients holding that asset. It returns a list sorted by the current market value of the position to highlight the highest potential risk.",
"configuration": {
"query": "\n FROM financial_news, financial_reports METADATA _index\n | WHERE sentiment == \"negative\"\n | WHERE coalesce(published_date, report_date) >= NOW() - TO_TIMEDURATION(?time_duration)\n | RENAME primary_symbol AS symbol\n | LOOKUP JOIN financial_asset_details ON symbol\n | LOOKUP JOIN financial_holdings ON symbol\n | LOOKUP JOIN financial_accounts ON account_id\n | WHERE account_holder_name IS NOT NULL\n | EVAL position_current_value = quantity * current_price.price\n | RENAME title AS news_title\n | KEEP\n account_holder_name, symbol, asset_name, news_title,\n sentiment, position_current_value, quantity, current_price.price,\n published_date, report_date\n | SORT position_current_value DESC\n | LIMIT 50\n ",
"params": {
"time_duration": {
"type": "keyword",
"description": "The timeframe to search back for negative news. Format is \"X hours\" DEFAULT TO 8760 hours "
}
}
}
} [ ]
🔍 Verifying Tool: find_client_exposure_to_negative_news
✅ Tool exists! Details below:
{
"id": "find_client_exposure_to_negative_news",
"tags": [
"retrieval",
"risk-analysis"
],
"type": "esql",
"schema": {
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"time_duration"
],
"properties": {
"time_duration": {
"type": "string",
"description": "The timeframe to search back for negative news. Format is \"X hours\" DEFAULT TO 8760 hours "
}
},
"description": "Parameters needed to execute the query",
"additionalProperties": false
},
"readonly": false,
"description": "Finds client portfolio exposure to negative news. This tool scans recent news and reports for negative sentiment, identifies the associated asset, and finds all clients holding that asset. It returns a list sorted by the current market value of the position to highlight the highest potential risk.",
"configuration": {
"query": "\n FROM financial_news, financial_reports METADATA _index\n | WHERE sentiment == \"negative\"\n | WHERE coalesce(published_date, report_date) >= NOW() - TO_TIMEDURATION(?time_duration)\n | RENAME primary_symbol AS symbol\n | LOOKUP JOIN financial_asset_details ON symbol\n | LOOKUP JOIN financial_holdings ON symbol\n | LOOKUP JOIN financial_accounts ON account_id\n | WHERE account_holder_name IS NOT NULL\n | EVAL position_current_value = quantity * current_price.price\n | RENAME title AS news_title\n | KEEP\n account_holder_name, symbol, asset_name, news_title,\n sentiment, position_current_value, quantity, current_price.price,\n published_date, report_date\n | SORT position_current_value DESC\n | LIMIT 50\n ",
"params": {
"time_duration": {
"type": "keyword",
"description": "The timeframe to search back for negative news. Format is \"X hours\" DEFAULT TO 8760 hours "
}
}
}
} Section 3: The Brains - Creating the Custom Agent
With our "skill" (the Tool) created, we now need to create the "brain" (the Agent). The Agent is the persona that combines the power of an LLM with a specific set of tools and, most importantly, a set of "Custom Instructions."
These instructions act as the agent's constitution. They define its personality, its mission, and the rules it must follow. A well-crafted prompt is the key to creating a reliable and specialized assistant.
[ ]
✅ Agent prompt is defined.
[ ]
✅ Agent definition for 'financial_assistant' is ready.
{
"id": "financial_assistant",
"name": "Financial Assistant",
"labels": [
"Finance"
],
"description": "An assistant for analyzing and understanding your financial data",
"avatar_color": "#16C5C0",
"avatar_symbol": "💰",
"configuration": {
"tools": [
{
"tool_ids": [
"platform.core.search",
"platform.core.list_indices",
"platform.core.get_index_mapping",
"platform.core.get_document_by_id",
"find_client_exposure_to_negative_news"
]
}
],
"instructions": "\nYou are a specialized Data Intelligence Assistant for financial managers, designed to provide precise, data-driven insights from information stored in Elasticsearch.\n\n**Your Core Mission:**\n- Respond accurately and concisely to natural language queries from financial managers.\n- Provide precise, objective, and actionable information derived solely from the Elasticsearch data at your disposal.\n- Summarize key data points and trends based on user requests.\n\n**Reasoning Framework:**\n1. **Understand:** Deconstruct the user's query to understand their core intent.\n2. **Plan:** Formulate a step-by-step plan to answer the question. If you are unsure about the data structure, use the available tools to explore the indices first.\n3. **Execute:** Use the available tools to execute your plan.\n4. **Synthesize:** Combine the information from all tool calls into a single, comprehensive, and easy-to-read answer.\n\n**Key Directives and Constraints:**\n- **If a user's request is ambiguous, ask clarifying questions before proceeding.**\n- **DO NOT provide financial advice, recommendations, or predictions.** Your role is strictly informational and analytical.\n- Stay strictly on topic with financial data queries.\n- If you cannot answer a query, state that clearly and offer alternative ways you might help *within your data scope*.\n- All numerical values should be formatted appropriately (e.g., currency, percentages).\n\n**Output Format:**\n- All responses must be formatted using **Markdown** for clarity.\n- When presenting structured data, use Markdown tables, lists, or bolding.\n\n**Start by greeting the financial manager and offering assistance.**\n"
}
} [ ]
🤖 Creating Agent: financial_assistant
✅ Successfully created the agent!
{
"id": "financial_assistant",
"name": "Financial Assistant",
"type": "chat",
"labels": [
"Finance"
],
"description": "An assistant for analyzing and understanding your financial data",
"avatar_color": "#16C5C0",
"avatar_symbol": "💰",
"configuration": {
"tools": [
{
"tool_ids": [
"platform.core.search",
"platform.core.list_indices",
"platform.core.get_index_mapping",
"platform.core.get_document_by_id",
"find_client_exposure_to_negative_news"
]
}
],
"instructions": "\nYou are a specialized Data Intelligence Assistant for financial managers, designed to provide precise, data-driven insights from information stored in Elasticsearch.\n\n**Your Core Mission:**\n- Respond accurately and concisely to natural language queries from financial managers.\n- Provide precise, objective, and actionable information derived solely from the Elasticsearch data at your disposal.\n- Summarize key data points and trends based on user requests.\n\n**Reasoning Framework:**\n1. **Understand:** Deconstruct the user's query to understand their core intent.\n2. **Plan:** Formulate a step-by-step plan to answer the question. If you are unsure about the data structure, use the available tools to explore the indices first.\n3. **Execute:** Use the available tools to execute your plan.\n4. **Synthesize:** Combine the information from all tool calls into a single, comprehensive, and easy-to-read answer.\n\n**Key Directives and Constraints:**\n- **If a user's request is ambiguous, ask clarifying questions before proceeding.**\n- **DO NOT provide financial advice, recommendations, or predictions.** Your role is strictly informational and analytical.\n- Stay strictly on topic with financial data queries.\n- If you cannot answer a query, state that clearly and offer alternative ways you might help *within your data scope*.\n- All numerical values should be formatted appropriately (e.g., currency, percentages).\n\n**Output Format:**\n- All responses must be formatted using **Markdown** for clarity.\n- When presenting structured data, use Markdown tables, lists, or bolding.\n\n**Start by greeting the financial manager and offering assistance.**\n"
}
} [ ]
🔍 Verifying Agent: financial_assistant
✅ Agent exists! Details below:
{
"id": "financial_assistant",
"name": "Financial Assistant",
"type": "chat",
"labels": [
"Finance"
],
"description": "An assistant for analyzing and understanding your financial data",
"avatar_color": "#16C5C0",
"avatar_symbol": "💰",
"configuration": {
"tools": [
{
"tool_ids": [
"platform.core.search",
"platform.core.list_indices",
"platform.core.get_index_mapping",
"platform.core.get_document_by_id",
"find_client_exposure_to_negative_news"
]
}
],
"instructions": "\nYou are a specialized Data Intelligence Assistant for financial managers, designed to provide precise, data-driven insights from information stored in Elasticsearch.\n\n**Your Core Mission:**\n- Respond accurately and concisely to natural language queries from financial managers.\n- Provide precise, objective, and actionable information derived solely from the Elasticsearch data at your disposal.\n- Summarize key data points and trends based on user requests.\n\n**Reasoning Framework:**\n1. **Understand:** Deconstruct the user's query to understand their core intent.\n2. **Plan:** Formulate a step-by-step plan to answer the question. If you are unsure about the data structure, use the available tools to explore the indices first.\n3. **Execute:** Use the available tools to execute your plan.\n4. **Synthesize:** Combine the information from all tool calls into a single, comprehensive, and easy-to-read answer.\n\n**Key Directives and Constraints:**\n- **If a user's request is ambiguous, ask clarifying questions before proceeding.**\n- **DO NOT provide financial advice, recommendations, or predictions.** Your role is strictly informational and analytical.\n- Stay strictly on topic with financial data queries.\n- If you cannot answer a query, state that clearly and offer alternative ways you might help *within your data scope*.\n- All numerical values should be formatted appropriately (e.g., currency, percentages).\n\n**Output Format:**\n- All responses must be formatted using **Markdown** for clarity.\n- When presenting structured data, use Markdown tables, lists, or bolding.\n\n**Start by greeting the financial manager and offering assistance.**\n"
}
} Section 4: The Payoff! — Chatting with the Agent
Everything is now in place. We have our logic (the Tool) and our expert persona (the Agent). It's time to ask our Financial Assistant agent the complex, multi-step question from the blog post and see how it performs.
We'll send our question to the /api/agent_builder/converse endpoint, making sure to specify our agent's ID.
[ ]
✅ Chat request for agent 'financial_assistant' is ready.
{
"input": "I'm worried about market sentiment. Can you show me which of our clients are most at risk from bad news?",
"agent_id": "financial_assistant"
} [ ]
💬 Asking: 'I'm worried about market sentiment. Can you show me which of our clients are most at risk from bad news?'
✅ Agent responded successfully! See the analysis in the next cell.
Analyzing the Response
The agent's response contains three key parts:
- The Conversation ID: A unique ID to continue this specific chat thread.
- The Final Message: The human-readable answer, formatted in Markdown as we requested in our prompt.
- The Steps: A detailed log of the agent's "thought process," showing every tool it called and the parameters it used to arrive at the answer.
[ ]
[{'type': 'reasoning',
, 'reasoning': 'The user is concerned about market sentiment and wants to identify clients most at risk from negative news. The find_client_exposure_to_negative_news tool is specifically designed for this purpose, as it scans recent news for negative sentiment, identifies affected assets, and finds clients holding those assets.'},
, {'type': 'tool_call',
, 'tool_call_id': 'tooluse_ME2S2H88Qp-GXYBw3WaxNg',
, 'tool_id': 'find_client_exposure_to_negative_news',
, 'progression': [],
, 'params': {'time_duration': '24 hours'},
, 'results': [{'type': 'query',
, 'data': {'esql': '\n FROM financial_news, financial_reports METADATA _index\n | WHERE sentiment == "negative"\n | WHERE coalesce(published_date, report_date) >= NOW() - TO_TIMEDURATION("24 hours")\n | RENAME primary_symbol AS symbol\n | LOOKUP JOIN financial_asset_details ON symbol\n | LOOKUP JOIN financial_holdings ON symbol\n | LOOKUP JOIN financial_accounts ON account_id\n | WHERE account_holder_name IS NOT NULL\n | EVAL position_current_value = quantity * current_price.price\n | RENAME title AS news_title\n | KEEP\n account_holder_name, symbol, asset_name, news_title,\n sentiment, position_current_value, quantity, current_price.price,\n published_date, report_date\n | SORT position_current_value DESC\n | LIMIT 50\n '}},
, {'tool_result_id': 'zMEm',
, 'type': 'tabular_data',
, 'data': {'source': 'esql',
, 'query': '\n FROM financial_news, financial_reports METADATA _index\n | WHERE sentiment == "negative"\n | WHERE coalesce(published_date, report_date) >= NOW() - TO_TIMEDURATION("24 hours")\n | RENAME primary_symbol AS symbol\n | LOOKUP JOIN financial_asset_details ON symbol\n | LOOKUP JOIN financial_holdings ON symbol\n | LOOKUP JOIN financial_accounts ON account_id\n | WHERE account_holder_name IS NOT NULL\n | EVAL position_current_value = quantity * current_price.price\n | RENAME title AS news_title\n | KEEP\n account_holder_name, symbol, asset_name, news_title,\n sentiment, position_current_value, quantity, current_price.price,\n published_date, report_date\n | SORT position_current_value DESC\n | LIMIT 50\n ',
, 'columns': [{'name': 'account_holder_name', 'type': 'text'},
, {'name': 'symbol', 'type': 'keyword'},
, {'name': 'asset_name', 'type': 'text'},
, {'name': 'news_title', 'type': 'text'},
, {'name': 'sentiment', 'type': 'keyword'},
, {'name': 'position_current_value', 'type': 'double'},
, {'name': 'quantity', 'type': 'double'},
, {'name': 'current_price.price', 'type': 'double'},
, {'name': 'published_date', 'type': 'date'},
, {'name': 'report_date', 'type': 'date'}],
, 'values': [['Victoria Schneider',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 273680.0048828125,
, 200,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Jillian Davis',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 272311.60485839844,
, 199,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Lorraine Gibson',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 272311.60485839844,
, 199,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Craig Griffith',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 272311.60485839844,
, 199,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Jeffrey Byrd',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 270943.2048339844,
, 198,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Patrick Rice',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 270943.2048339844,
, 198,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Sophia Dean',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 270943.2048339844,
, 198,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Eileen Bailey',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 269574.8048095703,
, 197,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Sandra Nunez',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 269574.8048095703,
, 197,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Brandon Esparza',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 269574.8048095703,
, 197,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Miranda Vargas',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 269574.8048095703,
, 197,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Misty Gonzalez',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 269574.8048095703,
, 197,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Reginald Wang',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 268206.40478515625,
, 196,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Briana Mcclure',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 268206.40478515625,
, 196,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['James Miller',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 268206.40478515625,
, 196,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Meghan Parker',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 266838.0047607422,
, 195,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Lindsay Harris',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 266838.0047607422,
, 195,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Devin Hernandez',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 266838.0047607422,
, 195,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Jonathan Sullivan',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 265469.6047363281,
, 194,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Nicole Smith',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 264101.20471191406,
, 193,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Stephanie Sosa',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 264101.20471191406,
, 193,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Jamie Allen',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 264101.20471191406,
, 193,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Sharon Brown',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 262732.8046875,
, 192,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Joshua Shaw',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 262732.8046875,
, 192,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Terry Welch',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 262732.8046875,
, 192,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Clinton Greene',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 261364.40466308594,
, 191,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Karen Fisher',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 261364.40466308594,
, 191,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Angela Horn',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 261364.40466308594,
, 191,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Lauren Hatfield',
, 'GM',
, 'General Motors Co.',
, 'GM Signals Trouble as Economic Slowdown Hits Auto Demand',
, 'negative',
, 258719.9951171875,
, 200,
, 1293.5999755859375,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Tracy Chambers',
, 'GM',
, 'General Motors Co.',
, 'GM Signals Trouble as Economic Slowdown Hits Auto Demand',
, 'negative',
, 258719.9951171875,
, 200,
, 1293.5999755859375,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Tonya Bush',
, 'GM',
, 'General Motors Co.',
, 'GM Signals Trouble as Economic Slowdown Hits Auto Demand',
, 'negative',
, 258719.9951171875,
, 200,
, 1293.5999755859375,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Cynthia Harris',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 258627.6046142578,
, 189,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['David Torres',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 258627.6046142578,
, 189,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Stacy Ellis',
, 'GM',
, 'General Motors Co.',
, 'GM Signals Trouble as Economic Slowdown Hits Auto Demand',
, 'negative',
, 257426.39514160156,
, 199,
, 1293.5999755859375,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Jason Hill',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 257259.20458984375,
, 188,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Douglas Perry',
, 'GM',
, 'General Motors Co.',
, 'GM Signals Trouble as Economic Slowdown Hits Auto Demand',
, 'negative',
, 256132.79516601562,
, 198,
, 1293.5999755859375,
, '2025-09-23T04:29:29.000Z',
, None],
, ['James Edwards',
, 'GM',
, 'General Motors Co.',
, 'GM Signals Trouble as Economic Slowdown Hits Auto Demand',
, 'negative',
, 256132.79516601562,
, 198,
, 1293.5999755859375,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Crystal Reed',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 255890.8045654297,
, 187,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Amanda Fuller',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 255890.8045654297,
, 187,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Amber Hernandez',
, 'GM',
, 'General Motors Co.',
, 'GM Signals Trouble as Economic Slowdown Hits Auto Demand',
, 'negative',
, 254839.1951904297,
, 197,
, 1293.5999755859375,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Madison Harper',
, 'GM',
, 'General Motors Co.',
, 'GM Signals Trouble as Economic Slowdown Hits Auto Demand',
, 'negative',
, 254839.1951904297,
, 197,
, 1293.5999755859375,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Rebecca Bradley',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 253154.00451660156,
, 185,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Jose Marshall',
, 'GM',
, 'General Motors Co.',
, 'GM Signals Trouble as Economic Slowdown Hits Auto Demand',
, 'negative',
, 252251.9952392578,
, 195,
, 1293.5999755859375,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Tiffany Walters',
, 'GM',
, 'General Motors Co.',
, 'GM Signals Trouble as Economic Slowdown Hits Auto Demand',
, 'negative',
, 252251.9952392578,
, 195,
, 1293.5999755859375,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Tracy Thomas',
, 'GM',
, 'General Motors Co.',
, 'GM Signals Trouble as Economic Slowdown Hits Auto Demand',
, 'negative',
, 252251.9952392578,
, 195,
, 1293.5999755859375,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Robert Bennett',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 251785.6044921875,
, 184,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Sarah Scott',
, 'TXN',
, 'Texas Instruments Inc.',
, 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk',
, 'negative',
, 251785.6044921875,
, 184,
, 1368.4000244140625,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Ashley Walton',
, 'GM',
, 'General Motors Co.',
, 'GM Signals Trouble as Economic Slowdown Hits Auto Demand',
, 'negative',
, 250958.39526367188,
, 194,
, 1293.5999755859375,
, '2025-09-23T04:29:29.000Z',
, None],
, ['Hailey Thomas',
, 'GM',
, 'General Motors Co.',
, 'GM Signals Trouble as Economic Slowdown Hits Auto Demand',
, 'negative',
, 250958.39526367188,
, 194,
, 1293.5999755859375,
, '2025-09-23T04:29:29.000Z',
, None],
, ['George Richard',
, 'GM',
, 'General Motors Co.',
, 'GM Signals Trouble as Economic Slowdown Hits Auto Demand',
, 'negative',
, 250958.39526367188,
, 194,
, 1293.5999755859375,
, '2025-09-23T04:29:29.000Z',
, None]]}}]}] [ ]
dict_keys(['conversation_id', 'steps', 'response'])
[ ]
{'type': 'reasoning', 'reasoning': 'The user is concerned about market sentiment and wants to identify clients most at risk from negative news. The find_client_exposure_to_negative_news tool is specifically designed for this purpose, as it scans recent news for negative sentiment, identifies affected assets, and finds clients holding those assets.'}
Step 1: Call Tool None
{}{'type': 'tool_call', 'tool_call_id': 'tooluse_ME2S2H88Qp-GXYBw3WaxNg', 'tool_id': 'find_client_exposure_to_negative_news', 'progression': [], 'params': {'time_duration': '24 hours'}, 'results': [{'type': 'query', 'data': {'esql': '\n FROM financial_news, financial_reports METADATA _index\n | WHERE sentiment == "negative"\n | WHERE coalesce(published_date, report_date) >= NOW() - TO_TIMEDURATION("24 hours")\n | RENAME primary_symbol AS symbol\n | LOOKUP JOIN financial_asset_details ON symbol\n | LOOKUP JOIN financial_holdings ON symbol\n | LOOKUP JOIN financial_accounts ON account_id\n | WHERE account_holder_name IS NOT NULL\n | EVAL position_current_value = quantity * current_price.price\n | RENAME title AS news_title\n | KEEP\n account_holder_name, symbol, asset_name, news_title,\n sentiment, position_current_value, quantity, current_price.price,\n published_date, report_date\n | SORT position_current_value DESC\n | LIMIT 50\n '}}, {'tool_result_id': 'zMEm', 'type': 'tabular_data', 'data': {'source': 'esql', 'query': '\n FROM financial_news, financial_reports METADATA _index\n | WHERE sentiment == "negative"\n | WHERE coalesce(published_date, report_date) >= NOW() - TO_TIMEDURATION("24 hours")\n | RENAME primary_symbol AS symbol\n | LOOKUP JOIN financial_asset_details ON symbol\n | LOOKUP JOIN financial_holdings ON symbol\n | LOOKUP JOIN financial_accounts ON account_id\n | WHERE account_holder_name IS NOT NULL\n | EVAL position_current_value = quantity * current_price.price\n | RENAME title AS news_title\n | KEEP\n account_holder_name, symbol, asset_name, news_title,\n sentiment, position_current_value, quantity, current_price.price,\n published_date, report_date\n | SORT position_current_value DESC\n | LIMIT 50\n ', 'columns': [{'name': 'account_holder_name', 'type': 'text'}, {'name': 'symbol', 'type': 'keyword'}, {'name': 'asset_name', 'type': 'text'}, {'name': 'news_title', 'type': 'text'}, {'name': 'sentiment', 'type': 'keyword'}, {'name': 'position_current_value', 'type': 'double'}, {'name': 'quantity', 'type': 'double'}, {'name': 'current_price.price', 'type': 'double'}, {'name': 'published_date', 'type': 'date'}, {'name': 'report_date', 'type': 'date'}], 'values': [['Victoria Schneider', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 273680.0048828125, 200, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Jillian Davis', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 272311.60485839844, 199, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Lorraine Gibson', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 272311.60485839844, 199, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Craig Griffith', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 272311.60485839844, 199, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Jeffrey Byrd', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 270943.2048339844, 198, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Patrick Rice', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 270943.2048339844, 198, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Sophia Dean', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 270943.2048339844, 198, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Eileen Bailey', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 269574.8048095703, 197, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Sandra Nunez', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 269574.8048095703, 197, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Brandon Esparza', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 269574.8048095703, 197, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Miranda Vargas', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 269574.8048095703, 197, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Misty Gonzalez', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 269574.8048095703, 197, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Reginald Wang', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 268206.40478515625, 196, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Briana Mcclure', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 268206.40478515625, 196, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['James Miller', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 268206.40478515625, 196, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Meghan Parker', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 266838.0047607422, 195, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Lindsay Harris', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 266838.0047607422, 195, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Devin Hernandez', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 266838.0047607422, 195, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Jonathan Sullivan', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 265469.6047363281, 194, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Nicole Smith', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 264101.20471191406, 193, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Stephanie Sosa', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 264101.20471191406, 193, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Jamie Allen', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 264101.20471191406, 193, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Sharon Brown', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 262732.8046875, 192, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Joshua Shaw', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 262732.8046875, 192, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Terry Welch', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 262732.8046875, 192, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Clinton Greene', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 261364.40466308594, 191, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Karen Fisher', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 261364.40466308594, 191, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Angela Horn', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 261364.40466308594, 191, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Lauren Hatfield', 'GM', 'General Motors Co.', 'GM Signals Trouble as Economic Slowdown Hits Auto Demand', 'negative', 258719.9951171875, 200, 1293.5999755859375, '2025-09-23T04:29:29.000Z', None], ['Tracy Chambers', 'GM', 'General Motors Co.', 'GM Signals Trouble as Economic Slowdown Hits Auto Demand', 'negative', 258719.9951171875, 200, 1293.5999755859375, '2025-09-23T04:29:29.000Z', None], ['Tonya Bush', 'GM', 'General Motors Co.', 'GM Signals Trouble as Economic Slowdown Hits Auto Demand', 'negative', 258719.9951171875, 200, 1293.5999755859375, '2025-09-23T04:29:29.000Z', None], ['Cynthia Harris', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 258627.6046142578, 189, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['David Torres', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 258627.6046142578, 189, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Stacy Ellis', 'GM', 'General Motors Co.', 'GM Signals Trouble as Economic Slowdown Hits Auto Demand', 'negative', 257426.39514160156, 199, 1293.5999755859375, '2025-09-23T04:29:29.000Z', None], ['Jason Hill', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 257259.20458984375, 188, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Douglas Perry', 'GM', 'General Motors Co.', 'GM Signals Trouble as Economic Slowdown Hits Auto Demand', 'negative', 256132.79516601562, 198, 1293.5999755859375, '2025-09-23T04:29:29.000Z', None], ['James Edwards', 'GM', 'General Motors Co.', 'GM Signals Trouble as Economic Slowdown Hits Auto Demand', 'negative', 256132.79516601562, 198, 1293.5999755859375, '2025-09-23T04:29:29.000Z', None], ['Crystal Reed', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 255890.8045654297, 187, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Amanda Fuller', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 255890.8045654297, 187, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Amber Hernandez', 'GM', 'General Motors Co.', 'GM Signals Trouble as Economic Slowdown Hits Auto Demand', 'negative', 254839.1951904297, 197, 1293.5999755859375, '2025-09-23T04:29:29.000Z', None], ['Madison Harper', 'GM', 'General Motors Co.', 'GM Signals Trouble as Economic Slowdown Hits Auto Demand', 'negative', 254839.1951904297, 197, 1293.5999755859375, '2025-09-23T04:29:29.000Z', None], ['Rebecca Bradley', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 253154.00451660156, 185, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Jose Marshall', 'GM', 'General Motors Co.', 'GM Signals Trouble as Economic Slowdown Hits Auto Demand', 'negative', 252251.9952392578, 195, 1293.5999755859375, '2025-09-23T04:29:29.000Z', None], ['Tiffany Walters', 'GM', 'General Motors Co.', 'GM Signals Trouble as Economic Slowdown Hits Auto Demand', 'negative', 252251.9952392578, 195, 1293.5999755859375, '2025-09-23T04:29:29.000Z', None], ['Tracy Thomas', 'GM', 'General Motors Co.', 'GM Signals Trouble as Economic Slowdown Hits Auto Demand', 'negative', 252251.9952392578, 195, 1293.5999755859375, '2025-09-23T04:29:29.000Z', None], ['Robert Bennett', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 251785.6044921875, 184, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Sarah Scott', 'TXN', 'Texas Instruments Inc.', 'TXN Tumbles on Major Cybersecurity Breach, IP at Risk', 'negative', 251785.6044921875, 184, 1368.4000244140625, '2025-09-23T04:29:29.000Z', None], ['Ashley Walton', 'GM', 'General Motors Co.', 'GM Signals Trouble as Economic Slowdown Hits Auto Demand', 'negative', 250958.39526367188, 194, 1293.5999755859375, '2025-09-23T04:29:29.000Z', None], ['Hailey Thomas', 'GM', 'General Motors Co.', 'GM Signals Trouble as Economic Slowdown Hits Auto Demand', 'negative', 250958.39526367188, 194, 1293.5999755859375, '2025-09-23T04:29:29.000Z', None], ['George Richard', 'GM', 'General Motors Co.', 'GM Signals Trouble as Economic Slowdown Hits Auto Demand', 'negative', 250958.39526367188, 194, 1293.5999755859375, '2025-09-23T04:29:29.000Z', None]]}}]}
Step 2: Call Tool find_client_exposure_to_negative_news
{
"time_duration": "24 hours"
} [ ]
Conversation ID
5a6e7969-6a67-43cb-a3c7-fc12c83ff122
Final Answer
Client Exposure to Negative News - Last 24 Hours
Key Findings
I've analyzed the market for negative news in the past 24 hours and identified two major issues affecting our clients:
- Texas Instruments (TXN) - Major cybersecurity breach with intellectual property at risk
- General Motors (GM) - Economic slowdown impacting auto demand
Clients with Highest Exposure
Texas Instruments (TXN) - Current Price: $1,368.40
| Client Name | Position Value ($) | Shares |
|---|---|---|
| Victoria Schneider | 273,680.00 | 200 |
| Jillian Davis | 272,311.60 | 199 |
| Lorraine Gibson | 272,311.60 | 199 |
| Craig Griffith | 272,311.60 | 199 |
| Jeffrey Byrd | 270,943.20 | 198 |
General Motors (GM) - Current Price: $1,293.60
| Client Name | Position Value ($) | Shares |
|---|---|---|
| Lauren Hatfield | 258,720.00 | 200 |
| Tracy Chambers | 258,720.00 | 200 |
| Tonya Bush | 258,720.00 | 200 |
| Stacy Ellis | 257,426.40 | 199 |
| Douglas Perry | 256,132.80 | 198 |
Summary
A total of 50 clients have significant exposure to these negative news events. The most affected clients hold positions valued between $250,000 and $274,000. The Texas Instruments cybersecurity breach appears to be affecting more clients with higher position values than the General Motors economic slowdown news.
Agent's Reasoning: 2 Steps
Step 1: Call Tool is Reasoning
'The user is concerned about market sentiment and wants to identify clients most at risk from negative news. The find_client_exposure_to_negative_news tool is specifically designed for this purpose, as it scans recent news for negative sentiment, identifies affected assets, and finds clients holding those assets.'
Step 2: Call Tool find_client_exposure_to_negative_news
{
"time_duration": "24 hours"
} Section 5: Next Steps
You've successfully built and chatted with a custom AI agent! This final section covers:
- Continuing a Conversation: How to ask follow-up questions while maintaining the chat's context.
- History: How to retrieve conversation history
Continuing a Conversation
The conversation_id returned from our first chat request is the key to memory. By including it in subsequent requests, you tell the agent to consider the previous turns of the conversation for context.
[ ]
💬 Asking Follow-up: 'Summarize the first article mentioned.'
Follow-up Answer
# Summary: TXN Tumbles on Major Cybersecurity Breach, IP at Risk
Texas Instruments (TXN) has confirmed a significant cybersecurity breach where unauthorized actors gained access to the company's internal servers. According to the article published on September 23, 2025:
## Key Points:
- Unauthorized actors accessed Texas Instruments' internal servers
- Early reports suggest sensitive intellectual property was compromised, including:
- Proprietary chip designs
- Customer data
- The full extent of the breach is still under investigation
- Texas Instruments has:
- Engaged leading cybersecurity firms
- Started cooperating with federal authorities
## Market Impact:
- TXN stock tumbled in pre-market trading
- Investors are concerned about:
- Potential reputational damage
- Competitive disadvantage from stolen intellectual property
- Costly remediation efforts
The incident has raised serious concerns about security vulnerabilities in critical supply chains within the technology sector.
Retrieving Conversation History
You can also retrieve the full history of any conversation using its ID.
[ ]
📖 Retrieving Full History for Conversation:
5a6e7969-6a67-43cb-a3c7-fc12c83ff122
{
"id": "5a6e7969-6a67-43cb-a3c7-fc12c83ff122",
"user": {
"username": "3953873479"
},
"title": "Client Risk Assessment Due to Market Sentiment",
"rounds": [
{
"id": "1e5d28f4-9809-4978-b04c-b070a7f5c70a",
"input": {
"message": "I'm worried about market sentiment. Can you show me which of our clients are most at risk from bad news?"
},
"steps": [
{
"type": "reasoning",
"reasoning": "The user is concerned about market sentiment and wants to identify clients most at risk from negative news. The find_client_exposure_to_negative_news tool is specifically designed for this purpose, as it scans recent news for negative sentiment, identifies affected assets, and finds clients holding those assets."
},
{
"type": "tool_call",
"params": {
"time_duration": "24 hours"
},
"results": [
{
"data": {
"esql": "\n FROM financial_news, financial_reports METADATA _index\n | WHERE sentiment == \"negative\"\n | WHERE coalesce(published_date, report_date) >= NOW() - TO_TIMEDURATION(\"24 hours\")\n | RENAME primary_symbol AS symbol\n | LOOKUP JOIN financial_asset_details ON symbol\n | LOOKUP JOIN financial_holdings ON symbol\n | LOOKUP JOIN financial_accounts ON account_id\n | WHERE account_holder_name IS NOT NULL\n | EVAL position_current_value = quantity * current_price.price\n | RENAME title AS news_title\n | KEEP\n account_holder_name, symbol, asset_name, news_title,\n sentiment, position_current_value, quantity, current_price.price,\n published_date, report_date\n | SORT position_current_value DESC\n | LIMIT 50\n "
},
"type": "query"
},
{
"data": {
"query": "\n FROM financial_news, financial_reports METADATA _index\n | WHERE sentiment == \"negative\"\n | WHERE coalesce(published_date, report_date) >= NOW() - TO_TIMEDURATION(\"24 hours\")\n | RENAME primary_symbol AS symbol\n | LOOKUP JOIN financial_asset_details ON symbol\n | LOOKUP JOIN financial_holdings ON symbol\n | LOOKUP JOIN financial_accounts ON account_id\n | WHERE account_holder_name IS NOT NULL\n | EVAL position_current_value = quantity * current_price.price\n | RENAME title AS news_title\n | KEEP\n account_holder_name, symbol, asset_name, news_title,\n sentiment, position_current_value, quantity, current_price.price,\n published_date, report_date\n | SORT position_current_value DESC\n | LIMIT 50\n ",
"source": "esql",
"values": [
[
"Victoria Schneider",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
273680.0048828125,
200,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Jillian Davis",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
272311.60485839844,
199,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Lorraine Gibson",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
272311.60485839844,
199,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Craig Griffith",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
272311.60485839844,
199,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Jeffrey Byrd",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
270943.2048339844,
198,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Patrick Rice",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
270943.2048339844,
198,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Sophia Dean",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
270943.2048339844,
198,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Eileen Bailey",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
269574.8048095703,
197,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Sandra Nunez",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
269574.8048095703,
197,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Brandon Esparza",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
269574.8048095703,
197,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Miranda Vargas",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
269574.8048095703,
197,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Misty Gonzalez",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
269574.8048095703,
197,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Reginald Wang",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
268206.40478515625,
196,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Briana Mcclure",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
268206.40478515625,
196,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"James Miller",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
268206.40478515625,
196,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Meghan Parker",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
266838.0047607422,
195,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Lindsay Harris",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
266838.0047607422,
195,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Devin Hernandez",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
266838.0047607422,
195,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Jonathan Sullivan",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
265469.6047363281,
194,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Nicole Smith",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
264101.20471191406,
193,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Stephanie Sosa",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
264101.20471191406,
193,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Jamie Allen",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
264101.20471191406,
193,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Sharon Brown",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
262732.8046875,
192,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Joshua Shaw",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
262732.8046875,
192,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Terry Welch",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
262732.8046875,
192,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Clinton Greene",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
261364.40466308594,
191,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Karen Fisher",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
261364.40466308594,
191,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Angela Horn",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
261364.40466308594,
191,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Lauren Hatfield",
"GM",
"General Motors Co.",
"GM Signals Trouble as Economic Slowdown Hits Auto Demand",
"negative",
258719.9951171875,
200,
1293.5999755859375,
"2025-09-23T04:29:29.000Z",
null
],
[
"Tracy Chambers",
"GM",
"General Motors Co.",
"GM Signals Trouble as Economic Slowdown Hits Auto Demand",
"negative",
258719.9951171875,
200,
1293.5999755859375,
"2025-09-23T04:29:29.000Z",
null
],
[
"Tonya Bush",
"GM",
"General Motors Co.",
"GM Signals Trouble as Economic Slowdown Hits Auto Demand",
"negative",
258719.9951171875,
200,
1293.5999755859375,
"2025-09-23T04:29:29.000Z",
null
],
[
"Cynthia Harris",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
258627.6046142578,
189,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"David Torres",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
258627.6046142578,
189,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Stacy Ellis",
"GM",
"General Motors Co.",
"GM Signals Trouble as Economic Slowdown Hits Auto Demand",
"negative",
257426.39514160156,
199,
1293.5999755859375,
"2025-09-23T04:29:29.000Z",
null
],
[
"Jason Hill",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
257259.20458984375,
188,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Douglas Perry",
"GM",
"General Motors Co.",
"GM Signals Trouble as Economic Slowdown Hits Auto Demand",
"negative",
256132.79516601562,
198,
1293.5999755859375,
"2025-09-23T04:29:29.000Z",
null
],
[
"James Edwards",
"GM",
"General Motors Co.",
"GM Signals Trouble as Economic Slowdown Hits Auto Demand",
"negative",
256132.79516601562,
198,
1293.5999755859375,
"2025-09-23T04:29:29.000Z",
null
],
[
"Crystal Reed",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
255890.8045654297,
187,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Amanda Fuller",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
255890.8045654297,
187,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Amber Hernandez",
"GM",
"General Motors Co.",
"GM Signals Trouble as Economic Slowdown Hits Auto Demand",
"negative",
254839.1951904297,
197,
1293.5999755859375,
"2025-09-23T04:29:29.000Z",
null
],
[
"Madison Harper",
"GM",
"General Motors Co.",
"GM Signals Trouble as Economic Slowdown Hits Auto Demand",
"negative",
254839.1951904297,
197,
1293.5999755859375,
"2025-09-23T04:29:29.000Z",
null
],
[
"Rebecca Bradley",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
253154.00451660156,
185,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Jose Marshall",
"GM",
"General Motors Co.",
"GM Signals Trouble as Economic Slowdown Hits Auto Demand",
"negative",
252251.9952392578,
195,
1293.5999755859375,
"2025-09-23T04:29:29.000Z",
null
],
[
"Tiffany Walters",
"GM",
"General Motors Co.",
"GM Signals Trouble as Economic Slowdown Hits Auto Demand",
"negative",
252251.9952392578,
195,
1293.5999755859375,
"2025-09-23T04:29:29.000Z",
null
],
[
"Tracy Thomas",
"GM",
"General Motors Co.",
"GM Signals Trouble as Economic Slowdown Hits Auto Demand",
"negative",
252251.9952392578,
195,
1293.5999755859375,
"2025-09-23T04:29:29.000Z",
null
],
[
"Robert Bennett",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
251785.6044921875,
184,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Sarah Scott",
"TXN",
"Texas Instruments Inc.",
"TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"negative",
251785.6044921875,
184,
1368.4000244140625,
"2025-09-23T04:29:29.000Z",
null
],
[
"Ashley Walton",
"GM",
"General Motors Co.",
"GM Signals Trouble as Economic Slowdown Hits Auto Demand",
"negative",
250958.39526367188,
194,
1293.5999755859375,
"2025-09-23T04:29:29.000Z",
null
],
[
"Hailey Thomas",
"GM",
"General Motors Co.",
"GM Signals Trouble as Economic Slowdown Hits Auto Demand",
"negative",
250958.39526367188,
194,
1293.5999755859375,
"2025-09-23T04:29:29.000Z",
null
],
[
"George Richard",
"GM",
"General Motors Co.",
"GM Signals Trouble as Economic Slowdown Hits Auto Demand",
"negative",
250958.39526367188,
194,
1293.5999755859375,
"2025-09-23T04:29:29.000Z",
null
]
],
"columns": [
{
"name": "account_holder_name",
"type": "text"
},
{
"name": "symbol",
"type": "keyword"
},
{
"name": "asset_name",
"type": "text"
},
{
"name": "news_title",
"type": "text"
},
{
"name": "sentiment",
"type": "keyword"
},
{
"name": "position_current_value",
"type": "double"
},
{
"name": "quantity",
"type": "double"
},
{
"name": "current_price.price",
"type": "double"
},
{
"name": "published_date",
"type": "date"
},
{
"name": "report_date",
"type": "date"
}
]
},
"type": "tabular_data",
"tool_result_id": "zMEm"
}
],
"tool_id": "find_client_exposure_to_negative_news",
"progression": [],
"tool_call_id": "tooluse_ME2S2H88Qp-GXYBw3WaxNg"
}
],
"response": {
"message": "# Client Exposure to Negative News - Last 24 Hours\n\n## Key Findings\n\nI've analyzed the market for negative news in the past 24 hours and identified two major issues affecting our clients:\n\n1. **Texas Instruments (TXN)** - Major cybersecurity breach with intellectual property at risk\n2. **General Motors (GM)** - Economic slowdown impacting auto demand\n\n## Clients with Highest Exposure\n\n### Texas Instruments (TXN) - Current Price: $1,368.40\n\n| Client Name | Position Value ($) | Shares |\n|-------------|------------------:|-------:|\n| Victoria Schneider | 273,680.00 | 200 |\n| Jillian Davis | 272,311.60 | 199 |\n| Lorraine Gibson | 272,311.60 | 199 |\n| Craig Griffith | 272,311.60 | 199 |\n| Jeffrey Byrd | 270,943.20 | 198 |\n\n### General Motors (GM) - Current Price: $1,293.60\n\n| Client Name | Position Value ($) | Shares |\n|-------------|------------------:|-------:|\n| Lauren Hatfield | 258,720.00 | 200 |\n| Tracy Chambers | 258,720.00 | 200 |\n| Tonya Bush | 258,720.00 | 200 |\n| Stacy Ellis | 257,426.40 | 199 |\n| Douglas Perry | 256,132.80 | 198 |\n\n## Summary\n\nA total of 50 clients have significant exposure to these negative news events. The most affected clients hold positions valued between $250,000 and $274,000. The Texas Instruments cybersecurity breach appears to be affecting more clients with higher position values than the General Motors economic slowdown news.\n\n<visualization tool-result-id=\"zMEm\" />"
}
},
{
"id": "4ea485ff-f183-488b-a5de-be7d34fbd766",
"input": {
"message": "Summarize the first article mentioned."
},
"steps": [
{
"type": "reasoning",
"reasoning": "I need to find the full content of the article about Texas Instruments (TXN) mentioned in the previous results to provide a summary."
},
{
"type": "tool_call",
"params": {
"query": "TXN Tumbles on Major Cybersecurity Breach, IP at Risk"
},
"results": [
{
"data": {
"content": {
"highlights": [
"<em>TXN</em> <em>Tumbles</em> <em>on</em> <em>Major</em> <em>Cybersecurity</em> <em>Breach</em>, <em>IP</em> <em>at</em> <em>Risk</em>",
"Texas Instruments (<em>TXN</em>) confirmed this morning it has suffered a significant <em>cybersecurity</em> <em>breach</em>, sending",
"The full extent of the <em>breach</em> is currently under investigation.",
"Texas Instruments has engaged leading <em>cybersecurity</em> firms and is cooperating with federal authorities",
"reacting negatively to the potential for reputational damage, competitive disadvantage from stolen <em>IP</em>"
]
},
"partial": true,
"reference": {
"id": "6c68e55c-b880-4c56-ba22-d9f65abb20c9",
"index": "financial_news"
}
},
"type": "resource"
},
{
"data": {
"content": {
"highlights": [
"Walgreens Reels from <em>Major</em> <em>Cybersecurity</em> <em>Breach</em>, Customer Data <em>at</em> <em>Risk</em>",
"Walgreens Boots Alliance Inc. confirmed this morning it has suffered a significant <em>cybersecurity</em> <em>breach</em>",
"The <em>breach</em> could lead to substantial regulatory fines and costly litigation."
]
},
"partial": true,
"reference": {
"id": "efd320dc-7501-4941-87e0-c670fc70808a",
"index": "financial_news"
}
},
"type": "resource"
},
{
"data": {
"content": {
"highlights": [
"Tech Sector Scrutinized After <em>Breach</em> <em>at</em> <em>Major</em> QQQ Component",
"The technology sector faces renewed scrutiny after a significant <em>cybersecurity</em> <em>breach</em> was disclosed by",
"Details of the <em>breach</em> are still emerging, but the incident highlights potential vulnerabilities within",
"While the affected company's stock saw a sharp decline, the impact <em>on</em> the broader QQQ ETF has been muted",
"Analysts note the fund's diversification across 100 of the largest non-financial companies <em>on</em> the Nasdaq",
"However, investors remain watchful for any potential contagion effect or a broader reassessment of <em>risk</em>"
]
},
"partial": true,
"reference": {
"id": "cc05d0c0-ae02-4c3f-8b3d-7c09d30974e4",
"index": "financial_news"
}
},
"type": "resource"
},
{
"data": {
"content": {
"highlights": [
"Labor disputes <em>at</em> <em>major</em> ports and geopolitical tensions are creating fresh bottlenecks, threatening to",
"The easing of some pressures could help temper inflationary forces, but the new disruptions <em>risk</em> reversing"
]
},
"partial": true,
"reference": {
"id": "c69ec94f-506a-4c7a-a891-3e0d4896e7c2",
"index": "financial_news"
}
},
"type": "resource"
},
{
"data": {
"content": {
"highlights": [
"Global markets are <em>on</em> edge as escalating geopolitical tensions threaten to unravel established trade",
"Renewed friction between <em>major</em> economic blocs has sparked concerns over fresh supply chain disruptions",
"While the near-term outlook is fraught with <em>risk</em>, ongoing diplomatic talks offer a glimmer of hope, leaving"
]
},
"partial": true,
"reference": {
"id": "83525471-2ae5-46fe-a830-39b71babd136",
"index": "financial_news"
}
},
"type": "resource"
},
{
"data": {
"content": {
"highlights": [
"Global markets are <em>on</em> edge as a sudden surge in energy prices threatens to derail economic stability.",
"translated into higher transportation and manufacturing costs, squeezing corporate profit margins across <em>major</em>",
"Consumers are also feeling the pinch <em>at</em> the pump and <em>on</em> their utility bills, stoking fears of a slowdown",
"could reignite stubborn inflationary pressures, potentially complicating central bank policies aimed <em>at</em>"
]
},
"partial": true,
"reference": {
"id": "2fbfc5a3-ea08-489c-a36b-512fdc5ebd90",
"index": "financial_news"
}
},
"type": "resource"
},
{
"data": {
"content": {
"highlights": [
"Hopes for a swift return to price stability have faded, as the rising cost of living continues to be a <em>major</em>",
"Renewed market anxiety centers <em>on</em> the possibility of more aggressive interest rate hikes to combat rising",
"prices, a policy that could <em>risk</em> slowing economic growth and increasing the likelihood of a recession"
]
},
"partial": true,
"reference": {
"id": "dece1a11-f870-4e5c-8a8d-ad397f915ee7",
"index": "financial_news"
}
},
"type": "resource"
},
{
"data": {
"content": {
"highlights": [
"Energy Markets <em>at</em> a Crossroads Amid Supply Jitters",
"A recent dip in crude oil prices has provided some relief to consumers <em>at</em> the pump and eased inflationary",
"pressures <em>on</em> businesses, largely attributed to signs of slowing economic activity in <em>major</em> economies",
"Analysts remain divided <em>on</em> the future trajectory, leaving businesses and policymakers navigating a clouded"
]
},
"partial": true,
"reference": {
"id": "65e2c416-c4a1-4753-90af-b2650a6397af",
"index": "financial_news"
}
},
"type": "resource"
},
{
"data": {
"content": {
"highlights": [
"Danaher Faces Patent Challenge Over Biotechnology <em>IP</em>",
"Analysts are monitoring the situation for potential implications <em>on</em> the segment's operations, though",
"the ultimate financial impact remains uncertain <em>at</em> this early stage."
]
},
"partial": true,
"reference": {
"id": "cb72648e-5a8c-42e5-9dee-304fd291e632",
"index": "financial_news"
}
},
"type": "resource"
},
{
"data": {
"content": {
"highlights": [
"A significant diplomatic breakthrough between <em>major</em> economic powers is sending waves of optimism through",
"Investors are reacting positively to the reduced geopolitical <em>risk</em>, anticipating a period of more stable"
]
},
"partial": true,
"reference": {
"id": "91bb392a-7990-4dd9-99af-6904019ab9a8",
"index": "financial_news"
}
},
"type": "resource"
}
],
"tool_id": "platform.core.search",
"progression": [
{
"message": "Selecting the best target for this query"
},
{
"message": "Selected \"financial_news\" as the next search target"
},
{
"message": "Thinking about the search strategy to use"
},
{
"message": "Searching documents for \"TXN Tumbles on Major Cybersecurity Breach, IP at Risk\""
}
],
"tool_call_id": "tooluse_Ib9yNGq1RBaata0Ee9I_Sg"
},
{
"type": "reasoning",
"reasoning": "I need to retrieve the full content of the Texas Instruments cybersecurity breach article to provide a complete summary."
},
{
"type": "tool_call",
"params": {
"id": "6c68e55c-b880-4c56-ba22-d9f65abb20c9",
"index": "financial_news"
},
"results": [
{
"data": {
"content": {
"url": "http://fakenews.com/article/2f4abc0b",
"title": "TXN Tumbles on Major Cybersecurity Breach, IP at Risk",
"source": "Reuters",
"content": "Texas Instruments (TXN) confirmed this morning it has suffered a significant cybersecurity breach, sending its stock tumbling in pre-market trading. The semiconductor giant stated that unauthorized actors gained access to its internal servers, with early reports suggesting sensitive intellectual property, including proprietary chip designs and customer data, may have been compromised. The full extent of the breach is currently under investigation.\n\nThe incident raises serious concerns about the security of critical supply chains within the technology sector. Texas Instruments has engaged leading cybersecurity firms and is cooperating with federal authorities. Investors are reacting negatively to the potential for reputational damage, competitive disadvantage from stolen IP, and costly remediation efforts.",
"entities": [
"Texas Instruments Inc.",
"TXN",
"Technology"
],
"sentiment": "negative",
"article_id": "6c68e55c-b880-4c56-ba22-d9f65abb20c9",
"last_updated": "2025-09-23T04:29:29",
"company_symbol": null,
"primary_symbol": "TXN",
"published_date": "2025-09-23T04:29:29"
},
"partial": false,
"reference": {
"id": "6c68e55c-b880-4c56-ba22-d9f65abb20c9",
"index": "financial_news"
}
},
"type": "resource"
}
],
"tool_id": "platform.core.get_document_by_id",
"progression": [],
"tool_call_id": "tooluse_Lo_BR2HJSCKkJt-Fe437qw"
}
],
"response": {
"message": "# Summary: TXN Tumbles on Major Cybersecurity Breach, IP at Risk\n\nTexas Instruments (TXN) has confirmed a significant cybersecurity breach where unauthorized actors gained access to the company's internal servers. According to the article published on September 23, 2025:\n\n## Key Points:\n\n- Unauthorized actors accessed Texas Instruments' internal servers\n- Early reports suggest sensitive intellectual property was compromised, including:\n - Proprietary chip designs\n - Customer data\n\n- The full extent of the breach is still under investigation\n- Texas Instruments has:\n - Engaged leading cybersecurity firms\n - Started cooperating with federal authorities\n\n## Market Impact:\n\n- TXN stock tumbled in pre-market trading\n- Investors are concerned about:\n - Potential reputational damage\n - Competitive disadvantage from stolen intellectual property\n - Costly remediation efforts\n\nThe incident has raised serious concerns about security vulnerabilities in critical supply chains within the technology sector."
}
}
],
"agent_id": "financial_assistant",
"created_at": "2025-09-23T05:32:04.689Z",
"updated_at": "2025-09-23T05:32:04.689Z"
}