SKILLEMALL.ai

AF data-designer

Use when the user wants to create a dataset, generate synthetic data, or build a data generation pipeline.

ClawHub Claude Code author: NVIDIA 1 file body ≈ 1 113 tokens Open the sourceclawhub.ai analyzed 28 h ago

Do not explore the workspace first.

As a process F 67/100 · Will not run — References files that are not bundled: references/seed-datasets.md, references/person-sampling.md

GeneratorData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
F
67/100
Will not run
References files that are not bundled: references/seed-datasets.md, references/person-sampling.md
Tools and files w 18
0
Result and completion w 14
60
When it triggers w 12
70
the three weakest of ten parameters · all ten

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 · 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 missing-ref reference to a missing file: references/seed-datasets.md
  • warning missing-ref reference to a missing file: references/person-sampling.md

Process rating: all ten parameters 67/100

Will not run. References files that are not bundled: references/seed-datasets.md, references/person-sampling.md
  • 0Tools and files. 2 referenced file(s) missing: references/seed-datasets.md, references/person-sampling.md
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 12 steps, 2 vague phrases
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1113 tokens
  • 100Running it twice. Mutating operations check current state
  • 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)
  • +3Description length 106: 120–800 characters recommended
  • +2Single-language instructions
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 12 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.