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dynamodb_table_delete

Delete a DynamoDB table by specifying its name to remove unused or outdated data storage from AWS.

Instructions

Delete a DynamoDB table

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
table_nameYesName of the DynamoDB table

Implementation Reference

  • The core handler logic within handle_dynamodb_operations that performs the DynamoDB table deletion using the boto3 client.
    elif name == "dynamodb_table_delete":
        response = dynamodb_client.delete_table(
            TableName=arguments["table_name"])
  • Defines the Tool schema including inputSchema for validating the table_name parameter.
    Tool(
        name="dynamodb_table_delete",
        description="Delete a DynamoDB table",
        inputSchema={
            "type": "object",
            "properties": {
                "table_name": {
                    "type": "string",
                    "description": "Name of the DynamoDB table"
                }
            },
            "required": ["table_name"]
        }
    ),
  • Registers the tool by including it in the list_tools response via get_aws_tools() which sources from get_dynamodb_tools().
    async def list_tools() -> list[Tool]:
        """List available AWS tools"""
        logger.debug("Handling list_tools request")
        return get_aws_tools()
  • Dispatches calls to dynamodb_table_delete to the appropriate handler function based on name prefix.
    return await handle_dynamodb_operations(aws, name, arguments)
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. 'Delete a DynamoDB table' implies a destructive, irreversible operation, but it fails to specify critical details: whether authentication is required, if there are rate limits, what happens to the data (permanent loss), or if there's a confirmation step. For a high-risk mutation tool, this is a significant gap in transparency.

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 with zero wasted words. It's front-loaded with the core action ('Delete') and resource ('DynamoDB table'), making it immediately scannable. Every word earns its place in conveying the essential purpose.

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?

Given this is a destructive mutation tool with no annotations and no output schema, the description is incomplete. It doesn't address the high-risk nature of the operation, expected outcomes, error conditions, or how it differs from similar tools like 'dynamodb_item_delete'. For a tool that permanently destroys resources, more context is needed to use it safely and correctly.

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, with the single parameter 'table_name' clearly documented. The description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description.

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 ('Delete') and resource ('a DynamoDB table'), making the purpose immediately understandable. It distinguishes this tool from sibling tools like 'dynamodb_item_delete' by specifying table-level deletion rather than item-level. However, it doesn't explicitly contrast with 'dynamodb_table_update' or 'dynamodb_table_describe', which would have made it a perfect 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. It doesn't mention prerequisites (e.g., table must exist), consequences (e.g., data loss), or when to choose 'dynamodb_table_delete' over 'dynamodb_item_delete' for removing data. The agent must infer usage from the tool name alone.

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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