get_metric_assets

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

No annotations are provided, so the description carries the full burden. It discloses that data is 'updated every 24 hours,' indicating potential caching/staleness—a useful behavioral trait. However, it doesn't cover other aspects like error conditions, rate limits, authentication needs, or response format. The description is neutral and doesn't contradict any annotations.

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 highly concise and front-loaded: the first sentence states the core purpose, and the second adds critical behavioral context (update frequency). Both sentences earn their place with no wasted words, making it easy for an agent to parse quickly.

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 no annotations, 0 parameters, and no output schema, the description provides basic purpose and a key behavioral note (24-hour update). However, it lacks details on output format (e.g., list structure, error handling) and doesn't fully compensate for the absence of structured metadata. It's minimally adequate but leaves gaps for a read operation.

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?

The tool has 0 parameters, and schema description coverage is 100% (empty schema). The description doesn't need to add parameter semantics, but it implicitly suggests a metric identifier is required (though not parameterized). Since there are no parameters, a baseline of 4 is appropriate, as the description adequately explains the tool's function without parameter confusion.

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: 'Returns dashboards, monitors, notebooks, and SLOs that a metric is stored in.' It specifies the verb ('returns') and the resources returned (dashboards, monitors, notebooks, SLOs). However, it doesn't explicitly differentiate from sibling tools like 'get_metric' or 'get_metric_tags', which might retrieve metric metadata rather than where it's used.

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 minimal usage guidance. It mentions the data is 'updated every 24 hours,' which hints at potential staleness, but doesn't specify when to use this tool versus alternatives (e.g., for finding metric dependencies vs. querying metric values). No explicit when/when-not or alternative tool references are provided.

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