get_loki_labels

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves label names but does not describe the return format (e.g., list structure, pagination), error handling, rate limits, or authentication requirements. For a tool with zero annotation coverage, this is a significant gap in transparency, though it at least correctly implies a read-only operation without contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that efficiently conveys the tool's purpose without unnecessary words. It is front-loaded with the core action and resource, making it easy to parse. There is no wasted verbiage, earning a high score for conciseness.

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

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

Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details on behavior, output, or usage context. Without annotations or an output schema, more guidance would be beneficial, but it is not completely inadequate, aligning with a score of 3.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, meaning the input schema already documents all three parameters (datasourceUid, start, end) with descriptions. The description adds no additional meaning beyond the schema, such as explaining why start and end times might be optional or how they affect the label retrieval. Thus, it meets the baseline of 3 where the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get all label names available in a Loki datasource.' It specifies the verb ('Get'), resource ('label names'), and scope ('in a Loki datasource'), which is specific and actionable. However, it does not explicitly differentiate from sibling tools like 'get_loki_label_values' or 'get_prometheus_labels,' which prevents a score of 5.

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

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 versus alternatives. It does not mention sibling tools like 'get_loki_label_values' (for values of a specific label) or 'get_prometheus_labels' (for Prometheus instead of Loki), nor does it specify prerequisites or contexts for usage. This lack of comparative or contextual advice limits its utility for an AI agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.