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dynamodb_table_update

Modify DynamoDB table configurations to adjust attribute definitions and update table properties for AWS database management.

Instructions

Update a DynamoDB table

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
table_nameYesName of the DynamoDB table
attribute_definitionsYesUpdated attribute definitions

Implementation Reference

  • Executes the dynamodb_table_update tool by calling boto3's update_table with the provided table name and attribute definitions.
    elif name == "dynamodb_table_update":
        update_params = {
            "TableName": arguments["table_name"],
            "AttributeDefinitions": arguments["attribute_definitions"]
        }
        response = dynamodb_client.update_table(**update_params)
  • Defines the input schema for the dynamodb_table_update tool, requiring table_name and attribute_definitions.
    Tool(
        name="dynamodb_table_update",
        description="Update a DynamoDB table",
        inputSchema={
            "type": "object",
            "properties": {
                "table_name": {
                    "type": "string",
                    "description": "Name of the DynamoDB table"
                },
                "attribute_definitions": {
                    "type": "array",
                    "description": "Updated attribute definitions"
                }
            },
            "required": ["table_name", "attribute_definitions"]
        }
    ),
  • Registers the dynamodb_table_update tool (among others) with the MCP server by including it in the list returned from get_aws_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 full burden but offers minimal behavioral insight. It states 'Update' which implies a mutation operation, but doesn't disclose critical details like required permissions, whether updates are atomic/reversible, potential downtime during schema changes, or error conditions. For a table-level update tool with zero annotation coverage, this is inadequate.

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 maximally concise with a single, clear sentence that states the core functionality. There's no wasted verbiage or unnecessary elaboration. The structure is 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 table mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't address what happens during the update, what the response contains, potential side effects on existing data, or how this differs from item-level updates. The agent lacks crucial context for safe and 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?

Schema description coverage is 100%, providing complete parameter documentation in the structured schema. The description adds no additional parameter semantics beyond what's already in the schema - it doesn't explain the relationship between 'table_name' and 'attribute_definitions', provide examples of attribute definitions, or clarify what 'updated' means in this context. Baseline 3 is appropriate when 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 verb 'Update' and the resource 'DynamoDB table', making the purpose immediately understandable. It distinguishes from siblings like 'dynamodb_table_create' and 'dynamodb_table_delete' by specifying the update action. However, it doesn't specify what aspects of the table are updated beyond what's implied by parameters.

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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., table must exist), when to choose this over 'dynamodb_item_update' for data modifications, or any limitations compared to sibling tools like 'dynamodb_table_describe' for metadata retrieval.

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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