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jgstew

bigfix-root-mcp

by jgstew

client_query_submit

Submit a BigFix client fast query to evaluate relevance on specific computers, with targeting by all, IDs, names, or relevance expression.

Instructions

Submit a BigFix client (fast) query. Targeting: set exactly one of target_all, target_computer_ids, target_computer_names, or target_relevance (client relevance evaluated on each agent to decide applicability). Targeting is limited to the configured operator's scope, so target_all means all computers this operator can see, not necessarily all computers in BigFix.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
query_textYesClient relevance to evaluate on each targeted agent.
target_allNoTarget all computers.
target_relevanceNoClient relevance targeting expression.
target_computer_idsNoTarget these BigFix computer IDs.
target_computer_namesNoTarget these computer names.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full transparency burden. It discloses the non-obvious targeting constraint and that target_all is scoped by the operator's permissions, not the whole BigFix deployment. This is meaningful, though it does not discuss submission latency or polling 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?

Two dense sentences with high information density. Every phrase contributes, and the most essential usage rule (set exactly one target) is front-loaded.

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?

For a 5-parameter submission tool with no annotations, the description covers the main input constraints and a critical semantic caveat. An output schema exists, so return values need not be described. The only notable gap is the lack of a pointer to sibling tools for alternative query workflows.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds crucial extra semantics: mutual exclusivity of targeting parameters, target_relevance as an applicability expression, and the real meaning of target_all. These clarifications go beyond the schema property descriptions.

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

Purpose4/5

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

The description clearly states the action ('Submit a BigFix client (fast) query') and resource, and adds useful targeting detail. It distinguishes from session relevance by specifying 'client', but does not explicitly contrast with the sibling 'client_query' tool.

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?

It gives concrete invocation guidance: 'set exactly one of target_all, target_computer_ids, target_computer_names, or target_relevance' and clarifies the operator-scope limitation of target_all. It does not mention when to prefer this tool over siblings, so it misses the exclusion side.

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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