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ALTR MCP Server

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by altrsoftware

create_collection

Group classifiers into a collection to identify sensitive data patterns in database columns during classification jobs.

Instructions

Create a classifier collection to use for automated data discovery.

Collections group classifiers together for classification jobs. After creating a collection, you can run a classification job to automatically scan your database columns and identify which contain sensitive data patterns.

Typical workflow: Create a collection (or use existing "ALTR Managed"), then use it in create_job to scan your database. Review results with get_classification_report to see which columns were detected.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
collection_nameYesUnique name for the collection.
descriptionNoOptional human‑readable description.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the burden. It describes the creation action and grouping behavior, but doesn't disclose permissions, side effects, or reversibility. It's adequate but not rich.

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 well-structured and concise, with a clear purpose statement, explanation of the collection, and a typical workflow. Every sentence adds value without redundancy.

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 presence of an output schema, the description doesn't need to explain return values. It provides workflow context and integrates with sibling tools well. Minor gap in not describing permission requirements or destruction behavior.

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%, so the baseline is 3. The description adds minimal extra meaning beyond the schema, e.g., 'Unique name' slightly clarifies uniqueness, but doesn't elaborate on format or constraints.

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 classifier collection for automated data discovery, distinguishing it from sibling tools like add_classifiers_to_collection and create_job by placing it in a typical workflow.

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

Usage Guidelines5/5

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

The description explicitly outlines a typical workflow: create a collection (or use existing ALTR Managed), then use in create_job, then review with get_classification_report. This provides clear when-to-use and alternative guidance.

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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