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Chrome Enterprise Premium MCP Server

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by google

create_default_dlp_rules

Sets up default Chrome DLP rules for an organizational unit to audit generative AI visits, watermark sensitive sites, and warn before pasting on AI sites.

Instructions

Creates a "Starter Pack" of default Chrome DLP rules for a specific Organizational Unit. Rules included:

  1. Audit visits to Generative AI sites.

  2. Apply watermarks to sensitive sites (Gmail, Salesforce, Zendesk).

  3. Warn users before pasting content on Generative AI sites (Gemini is excluded from warning).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
orgUnitIdYesThe target Organizational Unit ID
customerIdNoThe Chrome customer ID (e.g. C012345).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
failedRulesYes
createdRulesYes
failureCountYes
successCountYes
Behavior2/5

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

With no annotations provided, the description carries full burden. It discloses the mutation (creates) and lists rules, but does not explain idempotency, whether rules are appended or replaced, or required permissions. This leaves significant behavioral ambiguity.

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?

The description is concise, using a bullet list for the included rules. It front-loads the core purpose and is easy to parse. Minor room for improvement by removing redundant phrasing.

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

Completeness3/5

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

Given the presence of an output schema and two parameters, the description covers the primary purpose and rules. However, it omits details like expected output format, behavior on re-run, and prerequisite customerId, making it slightly incomplete for a mutation 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 coverage is 100% with parameter descriptions. The description adds context about the rules created but does not clarify parameter-specific meaning beyond what the schema already provides. Baseline 3 is appropriate.

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 creates a 'Starter Pack' of default Chrome DLP rules for a specific Organizational Unit, listing the three specific rules included. This distinguishes it from siblings like create_chrome_dlp_rule which creates individual rules.

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?

The description explains what rules are created but does not explicitly state when to use this tool versus alternatives like create_chrome_dlp_rule for single rules or list_dlp_rules for reviewing. Usage context is implied but not explicit.

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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