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Binalyze AIR MCP Server

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by binalyze

create_amazon_s3_repository

Set up an Amazon S3 repository for storing digital forensics evidence within the Binalyze AIR platform, enabling secure evidence management.

Instructions

Create a new Amazon S3 repository for evidence storage

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesName for the Amazon S3 repository
regionYesAWS region (e.g. eu-west-1)
bucketYesS3 bucket name
accessKeyIdYesAWS access key ID
secretAccessKeyYesAWS secret access key
organizationIdsNoOrganization IDs to associate the repository with. Defaults to empty array.
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While 'Create' implies a write operation, the description doesn't mention what permissions are needed, whether this operation is idempotent, what happens on failure, or what the expected output looks like. For a creation tool with zero annotation coverage, this is insufficient.

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 a single, efficient sentence that communicates the core purpose without any wasted words. It's appropriately sized and front-loaded with the essential information.

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

Completeness2/5

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

For a creation tool with no annotations and no output schema, the description is inadequate. It doesn't explain what happens after creation (e.g., repository ID returned, error conditions), doesn't mention authentication requirements beyond the obvious access keys, and provides no behavioral context about this being a potentially sensitive operation.

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 has 100% description coverage, providing clear documentation for all 6 parameters. The description adds no additional parameter information beyond what's already in the schema, so it meets the baseline of 3 where the schema does the heavy lifting.

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

Purpose4/5

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

The description clearly states the action ('Create') and resource ('new Amazon S3 repository for evidence storage'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'update_amazon_s3_repository' or other repository creation tools like 'create_azure_storage_repository', which would require a 5.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'create_azure_storage_repository' or 'update_amazon_s3_repository'. There's no mention of prerequisites, dependencies, or typical scenarios for creating an S3 repository versus other storage options.

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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