SKILLEMALL.ai

BF nemo-fabric-integrate

Use this skill when integrating NVIDIA NeMo Fabric into a consumer application, service, evaluation harness, or platform through the typed Python SDK — translating the consumer's own application, job, or deployment config into an in-memory FabricConfig, choosing the single-invocation convenience API or an explicitly started runtime, validating with plan and doctor, and consuming normalized results, artifacts, and telemetry.

ClawHub Agent Skills author: NVIDIA 1 file body ≈ 5 328 tokens Open the sourceclawhub.ai analyzed 2 d ago

Use this skill when integrating NVIDIA NeMo Fabric into a consumer application, service, evaluation harness, or platform through the typed Python SDK —…

As a process F 38/100 · Will not run — References files that are not bundled: references/config-mapping.md, references/results-and-errors.md, references/sdk-api-inventory.md

IntegrationGitHubSoftware developmentWriting and documentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
63
Run on models
none yet
Process rating
F
38/100
Will not run
References files that are not bundled: references/config-mapping.md, references/results-and-errors.md, references/sdk-api-inventory.md
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. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  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 body-long SKILL.md body ≈ 5328 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: references/config-mapping.md
  • warning missing-ref reference to a missing file: references/results-and-errors.md
  • warning missing-ref reference to a missing file: references/sdk-api-inventory.md

Process rating: all ten parameters 38/100

Will not run. References files that are not bundled: references/config-mapping.md, references/results-and-errors.md, references/sdk-api-inventory.md
  • 0Tools and files. 3 referenced file(s) missing: references/config-mapping.md, references/results-and-errors.md, references/sdk-api-inventory.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 9 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 70Execution cost. Instruction body is 5328 tokens
  • 100Steps. 49 steps
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress

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 427: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 49 items
  • +4Has examples (4 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.