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antarpreetsinghbajwa

cep-mcp-server

create_word_list_detector

Create a word list detector to specify terms for Chrome DLP rule matching, providing a reusable building block for data protection.

Instructions

Creates a new DLP word list detector. Detectors are building blocks for DLP rules. After creating a detector, you must reference its resource name in a 'create_chrome_dlp_rule' condition (e.g., using the 'matches_detector' function).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
wordsYesA list of words to match. Total character count across all words must be 12500 or less.
customerIdNoThe Chrome customer ID (e.g. C012345)
descriptionNoAn optional description for the detector.
displayNameYesThe display name for the detector.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
detectorYes
Behavior3/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It adds context about the detector's role and how the result must be used, which is useful. However, it does not mention any side effects, permissions, idempotency, or failure modes that would be expected for a creation tool.

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?

The description is only two sentences. The first sentence states the core action, and the second provides actionable integration guidance. Every sentence earns its place, with no filler or repetition of schema details.

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 the tool's moderate complexity—four parameters, full schema coverage, and an output schema—the description adequately explains the tool's purpose and how to use the result. It could be improved by explicitly contrasting with regex/URL detectors or noting any prerequisites, but it is sufficiently complete for common usage.

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?

The input schema covers all four parameters with descriptions, including constraints like maxItems for words and maxLength for displayName. The description adds only a usage example ('matches_detector') and reinforces the required nature of displayName and words, but does not provide new parameter-level meaning.

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 'Creates a new DLP word list detector.' It uses a specific verb and resource, and the 'word list' qualifier distinguishes it from sibling tools like create_regex_detector and create_url_list_detector.

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?

The description explains that detectors are building blocks for DLP rules and explicitly instructs the user to reference the detector's resource name in a create_chrome_dlp_rule condition. This provides clear integration context, but it does not explicitly state when to prefer this over regex or URL detectors.

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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