Submit Python job

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

Annotations already declare readOnlyHint=false, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description usefully adds the dryRun-by-default preview behavior and the gpuCount>0 GPU trigger, but omits that an actual submission also requires dryRun=false plus confirm=true, and says nothing about auth/profile or side effects on the cluster.

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, front-loaded sentences with no filler. The terseness is appropriate to the format, though it sacrifices coverage for a tool with 17 parameters.

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 17-parameter, non-read-only submission tool with no output schema and 35% schema coverage, the description is far too thin. An agent must reconstruct most of the invocation semantics from the schema alone.

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 only 35% across 17 parameters, so the description must compensate, yet it only touches gpuCount and implicitly dryRun. Nothing is said about args, cpus, memGb, walltime, partition, modules, condaEnv, or allowUntypedGpu, leaving most of the surface undocumented.

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 — run a project .py file as a batch job — and notes the CPU/GPU branch. It is clear enough to distinguish from ris_submit_r_job or ris_submit_notebook_job, but it does not name those siblings 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?

Beyond stating that dryRun previews by default, there is no guidance on when to pick this tool over ris_run, ris_plan_run, or the many other ris_submit_* variants. No prerequisites or exclusions are given.

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