explore_sensor_metrics

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

With no annotations provided, the description carries full burden for behavioral disclosure. While it describes the grouping behavior ('grouped by subsystem'), it doesn't mention important aspects like whether this is a read-only operation, potential performance impact, authentication requirements, rate limits, or what the return format looks like. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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, well-structured sentence that efficiently communicates the tool's purpose without any wasted words. It's front-loaded with the core action and includes all essential information in a compact form.

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 (listing metrics with grouping), no annotations, and no output schema, the description provides adequate basic information but lacks details about return format, error conditions, or behavioral constraints. It's minimally viable but leaves gaps that could hinder effective tool selection and invocation.

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?

With 100% schema description coverage and only one parameter ('sensor' with clear description), the description doesn't need to add parameter details. The baseline is 3, but since there's only one parameter and the schema fully documents it, a score of 4 reflects that the description appropriately focuses on tool purpose rather than redundant parameter explanations.

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 action ('List all available Prometheus metric names'), the resource ('on a sensor'), and the grouping method ('grouped by subsystem'). It specifically distinguishes this from sibling tools like 'query_sensor_metric' (which queries specific metrics) and 'get_prometheus_metadata' (which gets metadata rather than listing metric names).

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 implies usage for discovering available metrics on a specific sensor, but doesn't explicitly state when to use this versus alternatives like 'get_prometheus_metadata' or 'query_sensor_metric'. It provides basic context but lacks explicit guidance on exclusions or prerequisites.

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