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baramundi MCP Server

by mikewegmann

search_job_definitions

Search for job definitions by name or type prefix (e.g., INST, DEINST, RUN) to locate installation, uninstall, script, or update jobs. Returns details including ID, name, type, folder, and category.

Instructions

    Sucht Job-Definitionen nach Name oder Typ (Präfix).
    Jobs folgen der Namenskonvention: INST: (Installation), DEINST: (Deinstallation),
    RUN: (Skript/Aktion), UPD: (Update), SCAN:, OS:, REG:, INV:.

    Args:
        query: Suchbegriff im Job-Namen (z.B. 'Chrome', 'Edge', 'Office').
               Leer = alle Jobs des angegebenen Typs.
        type: Job-Typ als Präfix oder Kurzname:
              'install' / 'INST:', 'uninstall' / 'DEINST:', 'run' / 'RUN:',
              'update' / 'UPD:', 'scan' / 'SCAN:', 'os' / 'OS:'.
              Leer = alle Typen durchsuchen.
        limit: Maximale Anzahl Ergebnisse (Standard: 30).

    Returns:
        Objekt mit 'data' (Job-Liste) und 'total'.
        Felder: id, name, displayName, type, folder, category.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNo
limitNo
queryNo
Behavior2/5

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

While the description details functionality and return format, it fails to disclose behavioral traits such as read-only nature, authentication requirements, or side effects. With no annotations provided, the description should compensate but does not.

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 concise, well-structured with a clear purpose, parameter list, and return value description. Every sentence provides valuable information without redundancy.

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?

Given the simple parameter set and absence of output schema, the description adequately covers input parameters and return format. It could mention pagination or ordering, but overall it is sufficiently complete for a search tool.

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 description adds significant meaning to all three parameters, explaining query as a search term with examples, type as prefix or short name with a predefined list, and limit as max results. This greatly compensates for the 0% schema description coverage.

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 searches job definitions by name or type (prefix), providing a specific verb-resource pairing. It distinguishes from siblings like list_job_definitions (which likely lists all) by specifying search capabilities.

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

Usage Guidelines3/5

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

The description explains when to use the tool (search by name/type), including behavior for empty query or type. However, it does not explicitly state when not to use it or provide alternatives like list_job_definitions for full listings.

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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