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dns_split_horizon

Detect split-horizon DNS by comparing external and internal resolver responses to reveal configuration inconsistencies.

Instructions

Detect split-horizon (split-brain) DNS configurations by comparing responses from multiple external resolvers and an optional internal resolver. Split-horizon DNS returns different answers based on the source of the query, commonly used to serve internal IPs to corporate networks and external IPs to the internet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesThe domain to test for split-horizon DNS (e.g. 'internal.company.com')
internal_resolverNoInternal/corporate DNS resolver IP to compare against external resolvers (e.g. '10.0.0.1')
Behavior3/5

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

Without annotations, the description carries the burden of explaining behavior. It explains the methodology (comparing external and optional internal resolvers) but does not disclose potential side effects, network usage, or requirements such as internet access or rate limits. It also doesn't state whether the operation is read-only, though 'Detect' implies non-intrusive behavior.

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 two sentences, with the first sentence delivering the core purpose and method, and the second providing a brief explanation of split-horizon DNS. Every word earns its place, making it concise and well-structured.

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

Completeness3/5

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

The tool is relatively simple with two parameters and no output schema. The description explains the purpose and method but does not mention what the tool returns (e.g., a boolean, a report, raw responses) or any edge cases like an unreachable internal_resolver. For a detection tool, this lack of output and error context leaves some gaps.

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 already provides detailed descriptions for both parameters (domain and internal_resolver), with 100% schema coverage. The description adds a little context by explaining the role of the internal resolver in the comparison, but it does not significantly enhance the schema's parameter semantics.

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 clearly states the tool's purpose: 'Detect split-horizon (split-brain) DNS configurations by comparing responses from multiple external resolvers and an optional internal resolver.' This is a specific verb ('Detect') with a specific resource ('split-horizon DNS configurations') and a distinct method, setting it apart from sibling tools like dns_lookup or dns_reverse.

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 clearly implies when to use the tool (when split-horizon DNS is suspected) and provides context on how it works. It does not explicitly name alternatives or exclusions, but the scope is specific enough that an agent can infer appropriate use compared to other DNS-focused tools.

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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