job_metrics

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

The annotations already declare this as a read-only, idempotent, non-destructive, open-world operation, so the description's remaining job is to add behavior. The lazily fetched metrics / first-call latency warning is exactly the kind of context annotations cannot convey and is the strongest part of the definition. However, it tells nothing about output shape beyond what the output schema carries or about limits on the number of names requested.

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?

Three short sentences, front-loaded with the resource and the primary mode switch, with no filler. The latency note earns its place as an agent-operational caveat.

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?

An output schema exists, so return-value documentation is not required, and the core invocation pattern (list vs read, plus search narrowing) is fully covered. The remaining gap is guidance on the `cluster` parameter and any cap on how many metric names can be requested at once.

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 0%, so the description must carry the parameter burden; it does explain `names` and `search` with a usage example. But `cluster` is completely unexplained in both schema and description, and `job_id` is left entirely implicit, so two of four parameters get no semantic help.

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 opens with a specific resource, "Job-level metrics", and the rest of the text makes the verb clear (read metric values or list metric ids). The "job-level" qualifier implicitly separates it from the sibling vertex_metrics, but the description never names that sibling explicitly.

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 gives clear branch guidance: pass `names` to read values, omit it to enumerate available metric ids, and use `search` to narrow the id listing, with a concrete example ("checkpoint"). It lacks an explicit statement of when to prefer vertex_metrics or checkpoint_stats instead, so the alternative selection is implied rather than stated.

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