ZEN SecDB

linux_os

List supported Linux operating systems and their corresponding versions for use with the linux_audit tool.

What this tool does

Returns an array of supported OS/version pairs, each in the form:

{"os":"name", "versions":["version or codename"]}

This allows the LLM and the user to know exactly which inputs are valid for the linux_audit tool.

When to use this tool

Use this tool when:

the user does not know which OS names or versions are supported
the user provides unclear or ambiguous OS information
you need to validate os/version before performing a Linux audit

This tool should typically be called before linux_audit whenever parameters are uncertain.

Inputs

This tool does not require any input.

Outputs

Returns an array of objects:

os: supported Linux distribution identifier
versions: corresponding list of supported release or codename

Example:

[
    {"os": "ubuntu", "versions": ["noble","focal"]},
    {"os": "debian", "versions": ["bookworm","sid"]},
    {"os": "redhat", "version": ["redhat-9.0"]}
]

LLM usage guidelines

Use this tool to validate or suggest correct OS/version combinations before calling linux_audit.
If the user provides invalid or misspelled OS names, retrieve the official list here and ask them to select one.
Do not guess operating system identifiers-always rely on this tool to confirm correctness.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description	Default
`supported`	No

TDQS

A4.7/5.0

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. It discloses that the tool requires no input, returns an array of objects, and shows the output format with an example. It also clarifies its non-destructive, informational nature and warns against guessing OS identifiers. It could explicitly state there are no side effects or that it is a static list, but the behavior is well understood from the description.

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

Conciseness4/5

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

The description is well-structured with clear headings, bullet points, and an example. It is longer than necessary but each section adds value: what it does, when to use, inputs, outputs, and LLM guidelines. It is front-loaded with the main purpose, making it easy to scan.

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

Completeness5/5

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

The description is complete given the tool's simplicity. It fully explains the purpose, output format, and usage context, and the inclusion of an example provides concrete guidance. Since there is no input schema beyond '{}', there are no gaps, and the output is fully described.

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

Parameters5/5

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

The tool has zero parameters, and the description explicitly states 'This tool does not require any input.' This exceeds the baseline for 0-parameter tools by confirming there is nothing to provide, eliminating any ambiguity.

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 'List supported Linux operating systems and their corresponding versions for use with the linux_audit tool.' It specifies the exact resource (supported OS/version pairs) and distinguishes itself from sibling tools like linux_audit by noting it provides the valid inputs for that tool.

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

Usage Guidelines5/5

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

The description explicitly provides 'When to use this tool' with bullet points, states it 'should typically be called before linux_audit whenever parameters are uncertain,' and includes LLM usage guidelines that clarify when to use it for validation and correction. This is thorough alternative/context guidance.

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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TDQS

A4.7/5.0

Disambiguation4/5

Most tools have clearly distinct purposes (e.g., vulnerability_search for discovery, vulnerability_info for full details, vulnerability_score for CVSS/EPSS, epss_timeseries for history). However, pairs like vulnerability_info vs. vulnerability_score and linux_audit vs. purl_audit have overlapping functionality, though detailed descriptions help differentiate them.

Naming Consistency5/5

All tool names follow a consistent lowercase snake_case pattern with a descriptor and an operation noun (e.g., vulnerability_info, linux_audit, sightings_search, ssvc_calculator). No mixed conventions or stylistic deviations are present.

Tool Count5/5

The 11 tools are well-scoped for a vulnerability intelligence server, covering search, details, scoring, trends, audits, reports, and prioritization. The count is within the expected 3-15 range and each tool contributes a distinct capability.

Completeness5/5

The tool surface covers the full vulnerability intelligence lifecycle: discovery (vulnerability_search), detailed lookup (vulnerability_info), risk scoring (vulnerability_score), EPSS history, real-world sightings, SSVC prioritization, audits for both OS packages and application dependencies, and aggregated reports. No obvious dead-end or missing critical operation is apparent.

Resources

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