SKILLEMALL.ai

BF tao-run-platform

TAO Execution SDK for submitting and monitoring GPU training jobs on supported platforms (Brev, SLURM, local Docker, Kubernetes). Use when the user wants to run TAO jobs through the SDK, get job tracking, S3 I/O wrapping, multi-node distributed training, or platform-specific features that docker-run can't provide. Trigger phrases include "use the TAO SDK", "call tao_sdk", "AutoMLRunner", "ActionWorkflow", "Job handles", "S3 I/O wrapping", "TAO platform run".

ClawHub Agent Skills author: NVIDIA 1 file body ≈ 3 606 tokens Open the sourceclawhub.ai analyzed 19 h ago

TAO Execution SDK for submitting and monitoring GPU training jobs on supported platforms (Brev, SLURM, local Docker, Kubernetes).

As a process F 58/100 · Will not run — References files that are not bundled: references/spec-construction.md, references/orchestration-patterns.md, references/platform-notes.md

IntegrationDockerKubernetesInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
95
Quality 40%
78
Run on models
none yet
Process rating
F
58/100
Will not run
References files that are not bundled: references/spec-construction.md, references/orchestration-patterns.md, references/platform-notes.md
Tools and files w 18
0
Result and completion w 14
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. 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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Read Bash

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

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/spec-construction.md
  • warning missing-ref reference to a missing file: references/orchestration-patterns.md
  • warning missing-ref reference to a missing file: references/platform-notes.md
  • warning missing-ref reference to a missing file: references/error-patterns.md
  • warning missing-ref reference to a missing file: references/scope.md

Process rating: all ten parameters 58/100

Will not run. References files that are not bundled: references/spec-construction.md, references/orchestration-patterns.md, references/platform-notes.md
  • 0Tools and files. 5 referenced file(s) missing: references/spec-construction.md, references/orchestration-patterns.md, references/platform-notes.md
  • 0Result and completion. Does not say what the result is
  • 30Running it twice. 4 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 85Steps. 10 steps, 1 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Inputs and preconditions. Inputs and preconditions are listed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3606 tokens
  • 100Progress reporting. Reports progress
  • low 13 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (7 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

  • +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
  • +5Description quotes 7 example trigger phrases
  • +3Description length 462: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 10 items
  • +4Has examples (14 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.