Groq AI Agent Tool Call Audit in n8n Data Table Workflow
Groq AI Agent Tool Call Audit in n8n Data Table Workflow
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Groq AI Agent Tool Call Audit in n8n Data Table Workflow
Regular price
£20.99
Regular price
£20.99
Sale price
Unit price
/
per
Groq AI Agent “Flight Log” Audit Workflow for n8n Data Tables
This n8n workflow runs a chat-based Groq-powered support agent, captures every tool call into an n8n Data Table, and appends an audit note that flags any numbers in the final answer that aren’t supported by the question, tool inputs, or tool results.
What this workflow does
- Receives chat input via an n8n Chat trigger and starts/continues a session.
- Runs a Groq chat model with an agent that can call tools such as a Calculator and a demo order lookup tool, returning intermediate tool steps.
- Creates a log row per tool call in an n8n Data Table, including: session_id, logged_at, step_index, tool_name, tool_input, observation (tool output), and a final_answer_excerpt.
- Audits the final answer by checking whether each number in the response is supported by the question, the tool inputs, or the tool results, then writes an audit_note.
- Replies to the user with the agent’s answer plus a short flight-log line listing the tools used and the audit note.
Use cases
- Customer support QA: trace exactly how answers were produced, including tool inputs and outputs.
- Numbers verification: automatically flag unsupported figures in AI responses.
- SaaS operations: monitor agent behavior during order-status lookups (replace the demo order lookup with your real integration).
Technical details
-
Groq integration:
n8nn8n-nodes-langchainlm chat groqusing your Groq API credential. -
Agent + tools:
n8nn8n-nodes-langchainagentwith tool-calling (includes Calculator and a demo order lookup tool to be replaced). -
Logging: uses
data tablepluscode,sticky noteto transform intermediate steps into a structured “flight log.” - Schema mapping: configure Data Table columns for session_id, logged_at, step_index, tool_name, tool_input, observation, final_answer_excerpt, and audit_note.
-
Audit logic: implemented via
n8nn8n-nodes-langchaintool code/ code steps to validate number provenance.
Note: Update the demo order lookup tool with your real order-status lookup while keeping the same tool interface if desired.
