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dynamodb_batch_get

Retrieve multiple items from DynamoDB tables in a single operation to reduce API calls and improve data fetching efficiency.

Instructions

Batch get multiple items from DynamoDB tables

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
request_itemsYesMap of table names to keys to retrieve

Implementation Reference

  • Executes the dynamodb_batch_get tool by calling batch_get_item on the DynamoDB client with the provided request_items from arguments.
    elif name == "dynamodb_batch_get":
        response = dynamodb_client.batch_get_item(
            RequestItems=arguments["request_items"]
        )
  • Defines the input schema and metadata for the dynamodb_batch_get tool.
    Tool(
        name="dynamodb_batch_get",
        description="Batch get multiple items from DynamoDB tables",
        inputSchema={
            "type": "object",
            "properties": {
                "request_items": {
                    "type": "object",
                    "description": "Map of table names to keys to retrieve",
                    "additionalProperties": {
                        "type": "object",
                        "properties": {
                            "Keys": {
                                "type": "array",
                                "items": {
                                    "type": "object"
                                }
                            },
                            "ConsistentRead": {
                                "type": "boolean"
                            },
                            "ProjectionExpression": {
                                "type": "string"
                            }
                        },
                        "required": ["Keys"]
                    }
                }
            },
            "required": ["request_items"]
        }
    ),
  • Registers all AWS tools, including dynamodb_batch_get, by returning the list from get_aws_tools() in response to list_tools requests.
    @server.list_tools()
    async def list_tools() -> list[Tool]:
        """List available AWS tools"""
        logger.debug("Handling list_tools request")
        return get_aws_tools()
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 'batch get' implies a read operation, the description doesn't mention important behavioral aspects like rate limits, error handling for partial failures, response format, or whether this operation is eventually consistent by default. This leaves significant gaps for an agent trying to use the tool effectively.

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 functionality without any wasted words. It's appropriately sized for a tool with a clear primary function and good schema documentation.

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 batch operation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns, how errors are handled, performance characteristics, or limitations. Given the complexity implied by batch operations and the lack of structured metadata, the description should provide more complete context for effective use.

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?

With 100% schema description coverage, the schema already documents the single 'request_items' parameter thoroughly. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain the structure of the keys, provide examples, or clarify how multiple tables are handled. This meets the baseline for high schema coverage.

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 ('batch get') and resource ('multiple items from DynamoDB tables'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'dynamodb_item_get' (single-item retrieval) or 'dynamodb_item_query' (query-based retrieval), which would have earned a perfect score.

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. With multiple DynamoDB retrieval tools available (item_get, query, scan), the agent receives no help in selecting batch_get over these other options, nor any information about prerequisites or typical use cases.

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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