Data Anonymizer
Identify PII in datasets, generate anonymized versions, and verify compliance
Example Prompt
Scan the customers table for PII and create an anonymized version for the analytics team
About
Scans database tables for personally identifiable information such as names, emails, phone numbers, and addresses. It generates anonymized copies of the data using consistent pseudonymization, then verifies the anonymized output contains no residual PII. A compliance report documents what was found and how it was handled.
Workflow Steps
Query the source database to retrieve sample data and schema for PII detection
📊 Run SQL QueryReason through column names and data patterns to identify fields containing PII
🧠 Structured ReasoningWrite anonymized data into a local SQLite database using consistent pseudonymization
🗃️ Run SQLite QueryVerify the anonymized dataset and write a compliance report documenting all transformations
✏️ Write FileTools Used
Write File
Write or overwrite a file at a specified path with the given content
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
Run SQLite Query
Execute a SQL query against a local SQLite database file
Required MCP Servers
Filesystem
Read, search, and manage files on the local filesystem
PostgreSQL
Query, inspect, and manage PostgreSQL databases with full SQL support
Sequential Thinking
Dynamic problem-solving through structured thought sequences with branching and revision
SQLite
Query, inspect, and manage SQLite databases with full SQL support