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Code Gym AWS Emulator MCP

Code Gym AWS Emulator MCP

by B11-Health

dynamodb_delete_table

Destructive

Delete an emulated DynamoDB table to clean up local test environments without an AWS account. Use it when removing test tables or resetting sandbox state.

Instructions

Delete emulated DynamoDB table

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "table": "<table>"
    },
    "name": "dynamodb_delete_table"
  }
}

Input Schema

NameRequiredDescriptionDefault
tableYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0-beta.1

TDQS

C2.4/5.0
Behavior2/5

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

Annotations already declare destructiveHint=true and readOnlyHint=false, so the safety profile is covered; the description adds only the word "emulated", implying this targets a local emulator rather than real AWS. It says nothing about whether data is irrecoverably lost, whether deleting a missing table errors, or how to confirm success.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a single short, front-loaded phrase with no wasted words, but its brevity comes from under-specification rather than disciplined editing. It is appropriately sized, just too thin.

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?

This is a destructive mutation tool with no output schema and an undocumented parameter. An agent can guess what it does, but nothing in the definition covers failure modes, data loss implications, or the meaning of the sole argument.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There is a single required parameter with 0% schema description coverage, and the description never clarifies whether "table" is a table name, ARN, or identifier format. With the schema carrying no documentation, the description needed to compensate and does not.

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

Purpose3/5

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

The description gives a clear verb and resource ("Delete ... table"), but it largely restates the tool name, with "emulated" as the only added information. It does not differentiate this from siblings like s3_delete_bucket or sqs_delete_queue beyond the resource noun already in the name.

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?

There is no when-to-use or when-not-to-use guidance, no prerequisite (e.g., table must exist), and no pointer to dynamodb_list_tables or dynamodb_describe_table for verification. The agent must infer the context entirely from the name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.