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Create Dataset and Run Inference · aiskillstore | DecimalAI

ai mlby aiskillstore

Create Dataset and Run Inference

aiskillstore/fiftyone-dataset-inference

Source aiskillstore/marketplace ↗License Not recorded

Create a FiftyOne dataset from a directory of media files (images, videos, point clouds), optionally import labels in common formats (COCO, YOLO, VOC), run model inference, and store predictions.

SkillScore36Maintained

Automatic

AI Engineer pack

Last verified 8/22/2026

What it changes

Passed 5 of 14 test cases with the skill, and 3 of 14 without it.

Without skill18%

With skill36%

Checks it passed that the model alone missed

Executes @voxel51/zoo/apply_zoo_model operator.
Offers to run the missing package install command for the user.
Requests user confirmation on dataset name and label field parameters.

and 2 more in the full report

5 fixed3 passed either way13 still failing1 broke

Pass-rate lift: +18 pp
Tokens: +256%
Agent turns: 0%
Response time: 0%

Model gemini-3.6-flashMeasured 8/22/2026v18 of 22 cases passed with skill · 14 comparable

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/aiskillstore-fiftyone-dataset-inference/SKILL.md https://app.decimal.ai/s/aiskillstore-fiftyone-dataset-inference/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add aiskillstore-fiftyone-dataset-inference, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/aiskillstore-fiftyone-dataset-inference/ and pins it in .decimal/skills.lock

decimalai skills add aiskillstore-fiftyone-dataset-inference

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/aiskillstore-fiftyone-dataset-inference/SKILL.md https://app.decimal.ai/s/aiskillstore-fiftyone-dataset-inference/SKILL.md

Raw file: /s/aiskillstore-fiftyone-dataset-inference/SKILL.md ↗ · machine-readable summary at /s/aiskillstore-fiftyone-dataset-inference.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 5 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 5

Prompt

Run ImageNet classification on dataset 'pet_photos' using the PyTorch ResNet-50 zoo model to store predictions in field 'resnet_cls'.

What was checked, without and with the skill
Checked	Without skill	With skill
Executes @voxel51/zoo/apply_zoo_model with model set to resnet50-imagenet-torch.	Missed	Passed
Passes label_field parameter set to resnet_cls.	Passed	Passed

case-18 · gemini-3.6-flash · 8/22/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md403 linessingle file

Create Dataset and Run Inference

Overview

Create FiftyOne datasets from local directories, import labels in standard formats, and run model inference to generate predictions.

Use this skill when:

Loading images, videos, or point clouds from a directory
Importing labeled datasets (COCO, YOLO, VOC, CVAT, etc.)
Running model inference on media files
Building end-to-end ML pipelines

Prerequisites

FiftyOne MCP server installed and running
@voxel51/io plugin for importing data
@voxel51/zoo plugin for model inference
@voxel51/utils plugin for dataset management

Key Directives

ALWAYS follow these rules:

1. Explore directory first

Scan the user's directory before importing to detect media types and label formats.

2. Confirm with user

Present findings and get confirmation before creating datasets or running inference.

3. Set context before operations

set_context(dataset_name="my-dataset")

4. Launch App for inference

launch_app(dataset_name="my-dataset")

5. User specifies field names

Track record

Benchmark

5 / 14

test cases passed, vs 3 / 14 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

aiskillstore / marketplace

skills/adonaivera/fiftyone-dataset-inference/SKILL.md

View on GitHub ↗

Imported 8/3/2026Version v1

More skills from the same source and nearby in the registry, with their headline benchmark lift.

Ready to supercharge your AI agents?

See it in action

What's inside

Create Dataset and Run Inference

Overview

Prerequisites

Key Directives

1. Explore directory first

2. Confirm with user

3. Set context before operations

4. Launch App for inference

5. User specifies field names

Track record

Benchmark

Adoption

SkillSafety

Source

Related skills