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ThinAirTelematics

ThinAir Data

Official

pii_scan

Scan string columns across tables to identify common PII patterns like emails, SSNs, credit cards, and tokens using heuristic detection.

Instructions

Sweep string columns across tables for common PII patterns (email, SSN, credit card, phone, JWT, bearer tokens). Heuristic-only — not a compliance guarantee. [BUILD tier]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • bin/server.js:137-141 (registration)
    Registration of the 'pii_scan' tool in the static TOOLS array. Listed in the BUILD tier with a description of its PII-scanning capabilities and an empty input schema.
    {
      name: "pii_scan",
      description:
        "Sweep string columns across tables for common PII patterns (email, SSN, credit card, phone, JWT, bearer tokens). Heuristic-only — not a compliance guarantee. [BUILD tier]",
      inputSchema: { type: "object" },
  • Input schema for pii_scan: accepts only a generic object with no specific parameter requirements.
    inputSchema: { type: "object" },
  • Handler for all tool calls, including pii_scan. This is a static local adapter — instead of executing the tool, it returns a redirect message pointing users to the hosted MCP server at https://data.thinair.co/mcp for actual execution.
    server.setRequestHandler(CallToolRequestSchema, async () => ({
      content: [{ type: "text", text: REDIRECT_MESSAGE }],
      isError: false,
    }));
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so description carries burden. It clarifies heuristic nature, non-compliance, and BUILD tier, which adds context beyond basic functionality.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences front-load the main action and provide key caveats; no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no parameters or output schema, the description sufficiently explains what it does (scans for PII patterns) and its limitations (heuristic, no guarantee).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema is empty object (0 params), so baseline is 4. Description implies it operates on all string columns across tables, adding meaning beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool scans string columns for common PII patterns, listing specific examples (email, SSN, etc.), and distinguishes from sibling tools like data_profile or query_sql.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Caveats 'heuristic-only — not a compliance guarantee' are provided, but no explicit guidance on when to use vs alternatives like data_profile or detect_anomalies is given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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