Jupyter job

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

Annotations already declare readOnlyHint=false, destructiveHint=false, openWorldHint=true, so the safety profile is known. The description adds one genuine behavioral fact beyond the annotations — it does not open the tunnel itself — but it omits the critical dry-run-by-default workflow (dryRun defaults to true, confirm required for a real submit) despite the name implying submission.

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 short sentences, zero waste, with the core action and the key constraint front-loaded. Nothing redundant.

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 10-parameter mutation tool with no output schema and 40% schema coverage, the description is far too thin. It should explain the dry-run/confirm submission flow and at least gesture at resource parameters; as written, an agent could call it expecting a synchronous launch.

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?

With 10 parameters and only 40% schema description coverage, the description contributes nothing about parameters — no mention of gpu, cpus, memGb, walltime, profile, or the dryRun/confirm submission gate. The untyped fields like gpu, cpus, memGb, walltime, port, and account are left entirely to an under-documented schema.

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 states a specific verb and resource (launch JupyterLab on a compute node) plus a concrete return (SSH tunnel instructions). The closing sentence 'Never opens a tunnel itself' differentiates it from tunnel-oriented siblings like ris_open_ssh_master, though it does not distinguish it from ris_submit_notebook_job or ris_submit_python_job.

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: the mention of returned tunnel instructions suggests a follow-up step, but there is no explicit when-to-use statement and no routing against the many sibling submit_* tools. An agent must infer this is the JupyterLab-specific variant.

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