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run_workflow

Run a SLURM workflow from a YAML file, automatically handling job dependencies and parallel execution.

Instructions

Execute a SLURM workflow from a YAML file.

Jobs are executed in dependency order - independent jobs run in parallel,
dependent jobs wait for their prerequisites to complete.

Args:
    yaml_path: Path to the YAML workflow file
    from_job: Start execution from this job (skip earlier jobs)
    to_job: Stop execution at this job (skip later jobs)
    single_job: Execute only this specific job, ignoring dependencies
    dry_run: If true, show what would be executed without actually running
    args: Optional mapping merged over the YAML ``args`` section before
        Jinja rendering. ``python:`` prefix values are rejected.
    sweep: Optional sweep spec: ``{"matrix": {...}, "fail_fast": bool,
        "max_parallel": int}``. When present, the request goes through
        :class:`SweepOrchestrator` and the response contains
        ``sweep_run_id``.
    transport: Cluster selector — omit / "local" for local SLURM, or an
        SSH profile name to run against that remote cluster. Orthogonal to
        ``mount``: ``transport`` picks *which* cluster, ``mount`` picks the
        path-translation root within it.
    mount: Optional mount name within the SSH profile, enabling mount-aware
        path translation for ``work_dir`` / ``log_dir``. Requires an SSH
        ``transport``; passing ``mount`` with a local transport is an error.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argsNo
mountNo
sweepNo
to_jobNo
dry_runNo
from_jobNo
transportNo
yaml_pathYes
single_jobNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations, so description carries full burden. It discloses dependency-based execution order, parallel independent jobs, rejection of python: prefix in args, and sweep orchestration behavior. Missing details on auth or rate limits, but covers key behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Efficiently structured with a one-sentence summary followed by parameter explanations. Every sentence adds value; no redundant text despite covering 9 parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With output schema present, return values are likely covered. Description explains sweep response (sweep_run_id). For normal execution, it does not detail return, but schema fills gap. Overall complete for a complex tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so description must compensate. It does so thoroughly, explaining each parameter's purpose, constraints (e.g., mount requires SSH transport), and behavior (e.g., dry_run shows without executing).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description begins with a clear verb and resource: 'Execute a SLURM workflow from a YAML file.' It distinguishes from siblings like validate_workflow, create_workflow, and submit_job by focusing on execution with dependency ordering.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explains when to use parameters like from_job, to_job, single_job, dry_run, transport, mount, and sweep, and describes dependency ordering. However, it does not explicitly state when NOT to use this tool vs. alternatives like validate_workflow or submit_job.

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

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