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NightSquawk

tacticalrmm-mcp-server

by NightSquawk

List TacticalRMM Policies

tacticalrmm_list_policies
Read-onlyIdempotent

List automation policies from your TacticalRMM instance to review and audit automation configurations.

Instructions

List automation policies from /automation/policies/. This tool is read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of items to return.
offsetNoNumber of items to skip locally after receiving the API response.
response_formatNoOutput format: markdown for human-readable summaries, json for structured output.markdown
Behavior2/5

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

The description redundantly states 'This tool is read-only', which is already declared by annotations (readOnlyHint=true, destructiveHint=false). It adds no new behavioral context beyond annotations, such as pagination behavior, ordering, or what the response contains. The mention of the endpoint is more about purpose than behavior.

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 very short and front-loaded with the primary action. 'List automation policies from /automation/policies/' is concise and effective. However, the second sentence 'This tool is read-only' is redundant with existing annotations and does not earn its place, so it loses a point.

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 simple list tool with well-documented parameters and safety annotations, the description is mostly complete. It states what is listed and the source endpoint. However, it does not describe return format or pagination behavior, although these are partially addressed by parameters. Still, the description is adequate for an AI agent to select and invoke the tool correctly.

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 100% coverage with descriptions for all three parameters (limit, offset, response_format), so the baseline is 3. The description does not add any parameter information or clarify their usage beyond what the schema already specifies.

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 function with a specific verb 'List' and a specific resource 'automation policies', even specifying the endpoint '/automation/policies/'. This distinguishes it from sibling tools that list other entities like clients, agents, or sites.

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 notes the tool is read-only, which is a helpful safety cue, but it does not explicitly state when to use this tool over alternatives or provide exclusionary guidance. The intended use is largely implied by the tool name and the fact that it lists policies, but no explicit 'when to use' or 'instead of' instructions are given.

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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