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Submit a deck (inline files) and start it

submit_job

One call: create a hosted GPU job, upload the deck given INLINE as {relative_path: text}, and queue it. Total inline size <= 8 MB; for larger decks use create_job, PUT the tarball to upload_url, then start_job. Billing starts at the first heartbeat (state running) and stops at done/failed/cancelled. The deck is executed as a program on an isolated GPU pod.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gpuNoGPU class; call account for the offered classes and how jobs are priced. Default any = cheapest available
filesYesDeck contents: {"in.lmp": "...", "data.al": "..."}; paths relative, no '..'; must include `input`
inputYesRelative path of the LAMMPS (or runner) input script inside the deck, e.g. in.lmp
labelNoFree text <= 120 chars shown in job lists
launchNoLaunch template; omit for the default KOKKOS/CUDA LAMMPS command line
runnerNoRunner flavour: lammps (default) or openmm (beta)
estimate_sNoYour runtime guess in seconds; only used for the balance pre-check (min 900 s at the rate)
wall_limit_sNoHard cap in seconds (default 14400, max 86400); the job fails at the cap and is billed to it

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / gpu / description
      Previous value: -"GPU class; call account for the currently offered classes and hourly rates. Default any = cheapest available"New value: +"GPU class; call account for the offered classes and how jobs are priced. Default any = cheapest available"
  2. Changed2 schema fields changed
    • changedInput schema / properties / gpu / description
      Previous value: -"GPU class: any (cheapest available, default), rtx4090, a100 -- see account.rate_table"New value: +"GPU class; call account for the currently offered classes and hourly rates. Default any = cheapest available"
    • changedInput schema / properties / runner / description
      Previous value: -"Runner flavour: lammps (default) or openmm"New value: +"Runner flavour: lammps (default) or openmm (beta)"
  3. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations provide readOnly=false, destructive=false, and idempotent=false, but the description adds valuable behavioral context: the deck is executed as a program on an isolated GPU pod, and billing starts at the first running heartbeat and stops at terminal states. No contradiction with annotations.

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?

Four dense sentences, each earning its place: the one-call purpose, the size boundary and alternative path, and the billing/execution model. It is front-loaded and free of filler.

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?

For an 8-parameter tool with no output schema, the description plus fully covered schema is nearly complete. It captures the key boundary condition, alternative workflow, execution model, and billing behavior. A small gap is not stating what the response returns, but that does not block correct invocation.

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

Parameters4/5

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

Schema coverage is 100%, so a baseline of 3 applies. The description adds meaning beyond the schema by clarifying the inline nature of files, the 8 MB aggregate limit, and that the single call combines upload and queueing semantics.

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 states a specific composite operation: create a hosted GPU job, upload the inline deck, and queue it. It clearly distinguishes submit_job from the create_job + start_job workflow by framing it as 'One call'.

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

Usage Guidelines5/5

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

The description explicitly sets the inline size threshold (<= 8 MB) and directs agents to use create_job, PUT the tarball to upload_url, then start_job for larger decks. This is concrete when-to-use versus alternative guidance.

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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