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backup_drill

Verify a backup is restorable by booting its app in an isolated Docker environment, checking for a live response, then removing all temporary resources.

Instructions

Verify a backup by booting an app in an isolated Docker environment and checking that it responds. A second copy runs beside the live one on a network and port of its own, and everything it made is removed either way. A pass means the archive is not corrupt and the app starts on it, not that every row is there

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
allNoDrill all supported apps in the backup
appNoApp/service to drill (required unless all=true)
serverNoRemote server name from config (optional, runs locally if omitted)
archiveNoSpecific backup archive to verify (optional)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.18.1

TDQS

A4.2/5.0
Behavior4/5

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. It discloses that the tool runs an isolated Docker environment, creates a second copy, removes everything it made 'either way' (cleanup regardless of outcome), and clarifies the verification scope ('not that every row is there'). This is strong behavioral transparency for a verification tool.

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 three sentences with no wasted words. It front-loads the core purpose, then adds the isolation/cleanup behavior, then clarifies the verification scope. Every sentence earns its place.

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

Completeness4/5

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

The description is complete for a verification tool with no output schema. It explains the method, the cleanup behavior, and the meaning of a pass. It does not describe the return format or how to interpret failure, but the absence of an output schema and the simplicity of the tool make this a minor gap.

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%, so the schema already documents all four parameters. The description adds context about the overall behavior but does not add specific parameter-level meaning beyond what the schema provides. Baseline 3 is appropriate.

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

Purpose5/5

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

The description states a specific verb ('Verify a backup'), a resource ('backup'), and a method ('booting an app in an isolated Docker environment and checking that it responds'). It clearly distinguishes this from backup_create, backup_list, and backup_restore siblings by focusing on verification rather than creation, listing, or restoration.

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

Usage Guidelines4/5

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

The description explains what the tool does and its scope ('a second copy runs beside the live one on a network and port of its own'), and clarifies what a pass means. It does not explicitly name alternative tools or state when not to use it, but the context makes the verification use case clear. The 'required unless all=true' parameter note adds usage guidance.

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