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k9fr4n

thruk-mcp

by k9fr4n

thruk_stale_acks

List acknowledgements older than N days to identify stale or forgotten ones. Supports filtering by hostgroup and custom variables.

Instructions

Acknowledgements older than N days (potentially forgotten ones).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results (default 100).
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: custom_var, hostgroup Operators: eq, gte, in, lte, neq, regex Examples: # Objects in HG_AGILE: {"type":"leaf","field":"hostgroup","op":"eq","value":"HG_AGILE"} # 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.
min_daysNoMinimum acknowledgement age in days (default 7).
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 does not disclose that the tool is read-only, any required permissions, or what the response contains. The hint about 'potentially forgotten ones' is helpful but not sufficient for understanding behavioral traits like data mutability or side effects.

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 sentence, very concise. It front-loads the core concept. However, it could be restructured to explicitly state the verb and resource for even clearer communication.

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

Completeness2/5

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

No output schema is provided, and the description does not explain what the tool returns (e.g., a list of acknowledgements with fields). Given the tool retrieves data, this omission leaves the agent uncertain about the result format. The description also doesn't mention the significance of the default min_days 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 coverage is 100%, so the schema already documents all parameters well. The description adds no extra semantics beyond what the schema provides. It implicitly references 'min_days' via 'older than N days', but this is also covered in the schema. 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 clearly states the tool's purpose: listing acknowledgements older than N days. The phrase 'potentially forgotten ones' adds useful context. However, it could be more explicit by starting with a verb like 'List' instead of a noun phrase, which would improve clarity.

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?

No guidance is provided on when to use this tool versus alternatives like thruk_remove_acknowledgement or thruk_bulk_acknowledge. The agent must infer from the name and siblings, which is insufficient for effective selection.

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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