Data Quality Audit
Run validation queries to check for nulls, duplicates, and anomalies, then report findings
Example Prompt
Run a data quality audit on our production database and report any nulls or duplicates
About
This skill performs a comprehensive data quality audit by running validation queries against your database. It checks for null values in required fields, duplicate records, orphaned references, and statistical anomalies. The results are compiled into a clear report and shared with the team via Slack.
Workflow Steps
Run queries to detect null values in columns that should not allow them
📊 Run SQL QueryRun queries to find duplicate records across key tables
📊 Run SQL QueryAnalyze the query results to assess severity and identify root causes
🧠 Structured ReasoningStore the audit results in memory for historical trend comparison
🧠 Store MemorySend the data quality audit report to the team Slack channel
📨 Send MessageTools Used
Store Memory
Persist a key-value pair to the agent's long-term knowledge graph memory
Run SQL Query
Execute a read-only SQL query against a PostgreSQL database and return results
Structured Reasoning
Break down a complex problem into sequential reasoning steps with explicit chain-of-thought
Send Message
Send a message to a Slack channel or direct message conversation
Required MCP Servers
Memory (Knowledge Graph)
Persistent knowledge graph for storing and retrieving structured information across sessions
PostgreSQL
Query, inspect, and manage PostgreSQL databases with full SQL support
Sequential Thinking
Dynamic problem-solving through structured thought sequences with branching and revision
Slack
Send messages, read channels, and manage Slack workspace interactions