job_details

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint, so the safety profile is covered elsewhere. The description adds nothing beyond that — no note on what the cluster parameter does, whether the job must be running, or any cost/latency traits of an open-world lookup.

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?

A single short sentence with no filler and the resource identified up front. It is efficient, though efficiency here partly reflects under-specification rather than disciplined editing.

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 values need not be described. But with zero parameter documentation, no usage guidance, and an obscure optional cluster argument, the definition leaves too much for the agent to guess on a tool that is otherwise simple.

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% for two parameters. The description implies job_id via 'one job' but says nothing about the optional 'cluster' parameter, which is genuinely ambiguous (cluster name? ID? default null meaning?) and needs description-side explanation.

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 names the resource (one job) and the returned content (state and per-vertex status/parallelism), so the agent can roughly infer it is a detail-lookup tool. However, the phrasing is a noun fragment with no verb and no explicit differentiation from close siblings such as job_metrics, job_config, or job_timeline.

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?

There is no statement of when to call this versus job_metrics, job_config, job_timeline, or diagnose_job. The agent is left to infer usage purely from the one-line purpose statement.

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