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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds useful behavioral context: unknown metric_key values are rejected rather than silently accepted, and no site is needed. It does not describe return format, but with annotations present this is a strong addition.

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 front-loaded with the core purpose, then the critical usage instruction, then a compact list of metric categories. Every sentence earns its place by helping the agent select and correctly use the tool.

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 read-only listing tool with no output schema, the description is nearly complete: it states the purpose, the pre-create_goal use case, validation behavior, and metric coverage. It does not specify the exact return shape, but the metric categories and source hint are sufficient for correct 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?

Schema description coverage is 100%, so the detail parameter is already fully documented in the schema. The description does not mention the detail parameter or add any meaning beyond the schema, which makes the baseline 3 appropriate.

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 a specific verb (List) and resource (every metric a goal can be measured against) and adds scope (with where each one is read from). It clearly distinguishes itself from sibling tools like create_goal and list_goals by focusing on available metric definitions.

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?

It explicitly says to call this BEFORE create_goal and explains why: to pick a metric_key that is actually measured, because unknown keys are rejected. This gives a clear when-to-use condition and names the dependent sibling tool.

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