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k9fr4n

thruk-mcp

by k9fr4n

thruk_notification_summary

Count notifications grouped by contact, host, service, state, or group over a time window with optional filters.

Instructions

Count notifications grouped by a single dimension over a time window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinceNoStart of analysis window. Thruk relative time ("-2h", "-7d") or ISO datetime ("2026-05-21 14:00:00"). Default: last 24 h.-24h
untilNoEnd of the time window (same formats as since). Default: now.
filterNoStructured filter tree supporting AND/OR nesting. Two node types: leaf: {"type":"leaf", "field":"...", "op":"...", "value":...} group: {"type":"group", "operator":"and"|"or", "conditions":[...]} Available fields: contact, custom_var, host, hostgroup, service, since, state, until Operators: eq, gte, in, lte, neq, regex The 'since'/'until' fields accept Thruk relative time ("-2h", "-7d") or ISO datetime ("2026-05-21 14:00:00"). Examples: # Hosts DOWN in HG_AGILE: {"type":"group","operator":"and","conditions":[ {"type":"leaf","field":"hostgroup","op":"eq","value":"HG_AGILE"}, {"type":"leaf","field":"state","op":"eq","value":"down"} ]} # Hosts in HG_AGILE OR with KERNEL=windows: {"type":"group","operator":"or","conditions":[ {"type":"leaf","field":"hostgroup","op":"eq","value":"HG_AGILE"}, {"type":"leaf","field":"custom_var","op":"eq","value":{"var":"KERNEL","val":"windows"}} ]}
backendsNoComma-separated backend names (sites). Omit for all backends.
group_byNoDimension to group notification counts by: 'contact' (default), 'host', 'service', 'state', 'command', 'hostgroup' or 'servicegroup' (the last two: ventilation par client).contact
Behavior2/5

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

No annotations are provided, so the description carries full burden. It only states the action, omitting behavioral details such as read-only nature, permissions, rate limits, or output format. For a tool that performs aggregation, it adds no insight beyond the name.

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 a single concise sentence that front-loads the core action. It is appropriately sized for a tool with well-documented parameters, though it could benefit from a secondary sentence on output or usage distinction.

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

Completeness3/5

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

Given the tool has 5 parameters and no output schema, the description is minimal. It explains the counting and grouping but does not describe the output structure or indicate that the result is a mapping from dimension values to counts. The schema covers parameters well, but the description could be more complete about the return value.

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?

Schema description coverage is 100% (all 5 parameters have descriptions in the input schema). The tool description itself adds no parameter semantics; it repeats 'single dimension' which is already covered by the group_by parameter description. Baseline 3 is appropriate.

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 'Count notifications grouped by a single dimension over a time window' clearly states the action (count), resource (notifications), and the grouping aspect, which distinguishes it from sibling tools that list notifications or provide heatmaps. However, it could be more explicit about being an aggregation vs. a raw list, which would differentiate it further.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool vs. alternatives like thruk_notifications or thruk_list_notifications. It does not mention contexts where counting is preferred over listing, nor does it specify when not to use it (e.g., when raw data is needed).

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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