get_metrics_by_category

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

No annotations exist, so description carries the burden. It states the tool retrieves metrics and descriptions, which is a basic read behavior. However, it does not explicitly state it is a read operation, nor does it describe behavior for invalid categories or empty results.

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?

Two sentences with no wasted words. The Args section is structured clearly. Every sentence adds value.

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?

For a simple tool with one parameter and no output schema, the description sufficiently explains input and output (metrics with descriptions). Could mention what happens if category is invalid or missing, but overall adequate.

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 parameter 'category' has 0% schema description coverage, but the description's Args section adds 'The category name to retrieve metrics for.' This provides meaning beyond the schema's title alone. Could be improved with examples or expected format.

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 uses specific verb 'Get' and resource 'metrics in a specific category' with additional info 'with their descriptions'. It clearly distinguishes from sibling tools like get_dimensions_by_category (dimensions vs metrics) and list_metric_categories (categories vs metrics).

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?

No guidance is provided on when to use this tool versus alternatives, no prerequisites, no exclusions, and no context about categories or errors.

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