WhitePact

Generate PII Audit Report

rai_pii_report

Read-onlyIdempotent

Scan documents to generate a PII audit report that classifies findings, counts occurrences, scores privacy risk, and gives GDPR/CCPA remediation guidance for compliance evidence.

Instructions

Generate a detailed PII audit report for a document or corpus. Classifies findings by PII category (email, phone, SSN, credit card, IP, address), counts occurrences, computes a privacy risk score, and provides GDPR/CCPA remediation guidance. Used by Privacy Engineers for compliance evidence collection.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "texts": "<texts>"
    },
    "name": "rai_pii_report"
  }
}

Input Schema

Name	Required	Description	Default
`texts`	Yes	List of text documents to scan
`redact`	No	Include redacted versions in report
`context`	No	Context label: medical \| financial \| hr \| legal \| general	general

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.2.6Sep 11, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already establish the safety profile (readOnlyHint, idempotentHint, destructiveHint=false, closed world), so the description does not need to restate them. It adds useful behavioral context by disclosing the analytical pipeline and report contents (classification, counts, risk score, remediation guidance), which is more than the annotations convey. It stops short of stating rate limits, input size caps, or data retention behavior.

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

Conciseness4/5

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

Three tight sentences with zero filler, front-loaded on what the report is and what it contains. The trailing audience sentence is slightly less essential but still earns its place by anchoring the use case.

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?

With no output schema, the description correctly compensates by describing the report's contents and compliance framing. Annotations cover safety and determinism. Remaining gaps — whether input texts are persisted, size/throughput limits, and exact exit/return structure — are minor for a three-parameter read-only tool.

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

Parameters3/5

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

Schema description coverage is 100%, so all three parameters (texts, redact, context) are already fully documented in the schema. The description implies the scan input ('a document or corpus') and hints at redacted output, but it never explains the context parameter's enum-like label semantics (medical | financial | hr | legal | general) or how it affects classification. Baseline 3 is appropriate when the schema carries this burden.

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 gives a specific verb and resource ('Generate a detailed PII audit report') and then enumerates exactly what the report contains: PII category classification, occurrence counts, a privacy risk score, and GDPR/CCPA remediation guidance. This level of detail distinguishes it from generic siblings like rai_scan or rai_compliance without needing to name them.

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

Usage Guidelines4/5

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

It states a clear usage context ('Used by Privacy Engineers for compliance evidence collection'), which tells an agent when this tool is appropriate. However, it offers no explicit exclusions or named alternatives (e.g., when to prefer rai_scan or rai_compliance instead), so an agent must still infer the boundary.

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