slurm_submit_job

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

No annotations provided, so description carries full burden. It discloses write operation, audit logging, and dry_run behavior. However, it lacks details on resource allocation or potential failures.

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?

The description is well-structured with a summary paragraph and an Args list. It is concise for 13 parameters, though the summary slightly repeats the purpose.

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?

With 13 parameters, no output schema, and no annotations, the description provides good coverage of inputs and behavior. It lacks return value description and error handling, but is still fairly complete.

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%, but the description explains each parameter in detail (e.g., job_name, nodes, script) with Slurm flags. This adds significant meaning beyond the schema's types and titles.

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 clearly states the tool submits a multi-node GPU training job to Slurm via sbatch, generates the script, and submits it. It distinguishes from sibling tools like slurm_cancel_job or slurm_list_jobs.

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?

The description mentions dry_run for previewing and notes it's a write operation in audit log, but does not provide explicit when-not-to-use guidance or mention alternatives.

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