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AIops-tools

observability-aiops

loki_labels

List distinct Loki label names from a configurable lookback window, enabling quick identification of label keys for building queries and debugging observability data.

Instructions

[READ] Distinct Loki label names present in the lookback window.

Args: hours: Lookback window in hours (capped at the tool's max lookback). target: Loki target name from config; omit for the default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hoursNo
targetNo
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It does mention that hours are 'capped at the tool's max lookback' and that target defaults, which is useful. However, it omits how results are returned (e.g., sorted? includes internal labels?), any authentication/permission requirements, rate limits, or behavior on empty result sets. The [READ] prefix is a manual cue, not an annotation.

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 very concise: a one-line purpose followed by a compact argument list. Every sentence contributes meaningful information, with no redundancy or fluff. The structure is easy to scan and front-loads the purpose.

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's simplicity, the description gives enough to understand what it does and how to invoke it. However, without an output schema or annotations, it does not describe the return format or edge cases (e.g., empty results, error conditions). It also does not mention whether all label names are returned or only those from specific metric types. This leaves some gaps for an agent to fully rely on.

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 description coverage is 0%, so the description must compensate. It does explain both parameters with additional meaning: hours is a lookback window with a cap, target is a named Loki target from config and is optional with a default. This goes beyond the bare type information in the schema.

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 purpose: 'Distinct Loki label names present in the lookback window.' This uses a specific resource (Loki label names) and action (listing distinct names), distinguishing it from siblings like loki_label_values (which likely returns values for a given label) and loki_query/loki_tail_errors.

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 provides usage context for the parameters: 'hours: Lookback window in hours' and 'target: Loki target name from config; omit for the default.' However, it does not explicitly state when to use this tool versus alternatives, nor does it give exclusion criteria. The reader must infer its niche from the name and sibling tools.

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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