bigfix-root-mcp

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Qna List Targets

qna_list_targets

Lists targets available for client relevance evaluation and reports inventory path, auto-discovery status, and container target permission; listing does not probe or write.

Instructions

List targets available to qna_eval_client_relevance.

inventory_path is the inventory file in use: BIGFIX_QNA_INVENTORY when the server sets it, else the default search (~/.bigfix/remote_clients.toml, then the all-users config directory); null when none was found. A run that names no targets uses every inventory host. auto_discovery says whether qna_discover_targets is available (it probes local qna, container images and developer.bigfix.com, and adds what works to ~/.bigfix/remote_clients.toml); auto_discovery_pending says no inventory file exists yet, so the next run naming no targets discovers first without being asked. containers_allowed says whether arbitrary container image names may be passed as targets. Listing never probes or writes anything.

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.2.0Oct 20, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description carries the full behavioral burden and discloses the key side-effect profile: 'Listing never probes or writes anything.' It also explains auto_discovery_pending and discovery behavior on the next run, though it does not discuss permissions or output size.

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 purpose is front-loaded in the first sentence, and the remaining text is dense with useful behavioral context. It is somewhat long and explains output fields despite an output schema existing, but the sentences generally carry explanatory value.

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?

For a zero-parameter listing tool with an output schema, the definition is complete: it explains the resource, the inventory source, discovery implications, container target policy, and that listing has no probing or writing side effects.

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

Parameters4/5

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

The tool takes zero parameters, so there are no parameter semantics to document. The baseline for zero parameters is 4, and nothing in the description contradicts or obscures that.

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 and resource: 'List targets available to qna_eval_client_relevance.' It also names related siblings such as qna_discover_targets and clarifies the inventory context, so the agent can distinguish this tool from nearby qna tools.

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 relates the tool to qna_eval_client_relevance and explains that calling a run without named targets uses every inventory host or triggers discovery when no inventory exists. It names qna_discover_targets as a related alternative, though it does not give an explicit 'call this instead of that when...' rule.

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