ai_toolkit_status

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds that the call spans machine-level state (GPU VRAM/load, queues, active jobs) rather than one resource, which is useful scoping context. However, since an output schema exists, listing the reported sections largely restates the return payload, and no latency, auth, or freshness behavior is disclosed.

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 front-loaded sentence opens with the core purpose ('Connection check and machine overview') before the enumeration. No filler, no restatement of the tool name.

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 zero-parameter read-only tool with an output schema and readOnly/openWorld annotations, the description supplies enough to call it correctly. The only gap is guidance on when in a workflow to invoke it, which matters given the surrounding job-orchestration siblings.

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 takes zero parameters, so there is nothing for the description to disambiguate; baseline 4 applies. The description correctly implies a single parameterless call returning a full snapshot.

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 says specifically that this is a connection check plus machine overview, and enumerates the reported sections (GPUs with VRAM and load, queues, active jobs, data folders). That distinguishes it well from every sibling, all of which operate on a single job, dataset, or captions resource. It stops short of an explicit statement that nothing is mutated or filtered, but the intent is unambiguous.

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?

Usage is only implied: 'Connection check' hints at a diagnostic call to make before or instead of job operations, but the description never says when to call it, whether to call it first, or what to do if it fails. No sibling is named as an alternative or follow-up. An agent can infer it is a preflight/overview call but must guess at that.

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