SKILLEMALL.ai

BF nemo-mbridge-multi-node-slurm

Convert single-node scripts to multi-node Slurm sbatch jobs and debug common multi-node failures. Covers srun-native vs uv run torch.distributed approaches, container setup, NCCL timeouts, OOM sizing for MoE models, and interactive allocation.

ClawHub Agent Skills author: NVIDIA 1 file body ≈ 3 795 tokens Open the sourceclawhub.ai analyzed 28 h ago

Convert single-node scripts to multi-node Slurm sbatch jobs and debug common multi-node failures.

As a process F 35/100 · Will not run — References files that are not bundled: references/templates.md, examples/models/glm/glm_45v/slurm_sft.sh, examples/models/minimax/minimax_m2/slurm_conversion.sh

GeneratorSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
61
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: references/templates.md, examples/models/glm/glm_45v/slurm_sft.sh, examples/models/minimax/minimax_m2/slurm_conversion.sh
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: references/templates.md
  • warning missing-ref reference to a missing file: examples/models/glm/glm_45v/slurm_sft.sh
  • warning missing-ref reference to a missing file: examples/models/minimax/minimax_m2/slurm_conversion.sh
  • note edit-residue the text marks something as outdated (lines 29, 77, 126): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: references/templates.md, examples/models/glm/glm_45v/slurm_sft.sh, examples/models/minimax/minimax_m2/slurm_conversion.sh
  • 0Tools and files. 3 referenced file(s) missing: references/templates.md, examples/models/glm/glm_45v/slurm_sft.sh, examples/models/minimax/minimax_m2/slurm_conversion.sh
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 2 mutating operations with no state check
  • 100Steps. 30 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3795 tokens
  • 100Progress reporting. Reports progress
  • low The response is described with custom markup (4 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 243: enough signal without eating the budget
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 30 items
  • +4Has examples (18 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 61.