fiftyone-skills
codexBuild high-quality datasets and computer vision models. Visualize datasets, analyze models, find duplicates, run inference, evaluate predictions, and develop custom plugins.
19 skills · 2 commands · 1 MCP server
Run model inference on FiftyOne datasets using Zoo models or custom models. Use when applying ML models for detection, classification, segmentation, or embeddings on existing datasets.
Plugin fiftyone-dataset-inference from marketplace fiftyone-skills in voxel51/fiftyone-skills. Commands read from the repo's manifest — 12 days ago.
fiftyone-dataset-inferenceRun ML model inference on FiftyOne datasets. Use when running models for detection, classification, segmentation, or embeddings. Discovers available models dynamically from the Zoo, plugin operators, or custom sources — never assumes a fixed model list.
Build high-quality datasets and computer vision models. Visualize datasets, analyze models, find duplicates, run inference, evaluate predictions, and develop custom plugins.
19 skills · 2 commands · 1 MCP server
Drive the FiftyOne App via the Playwright MCP for operator/plugin verification, demo or screencast recording, and end-to-end UI automation against `fo.launch_app(...)`. Use when automating the FiftyOne App, recording an operator demo, or debugging a session that silently dies after a UI action (the `browser_navigate`-after-`reload_dataset` crash), covering launcher patterns (`remote=True`, trigger-file IPC), MUI input/dropdown gotchas, `data-cy` selectors, and scoped cleanup.
1 skill
Write Python code following FiftyOne's official conventions. Use when contributing to FiftyOne, developing plugins, or writing code that integrates with FiftyOne's codebase. Covers module structure, import organization, Google-style docstrings, lazy imports, guard patterns, and error handling.
1 skill
Creates Jupyter notebooks for FiftyOne workflows including getting-started guides, tutorials, recipes, and full ML pipelines. Use when users want to create a notebook, write a tutorial, build a demo, document a workflow, or generate a FiftyOne walkthrough covering data loading, exploration, inference, evaluation, and export. Builds notebooks cell-by-cell using NotebookEdit.
1 skill
End-to-end dataset curation for any FiftyOne dataset: inspect schema and media quality (blur, brightness, corruption, resolution), audit annotation quality (mistakenness, hardness, duplicate labels, IoU overlaps), analyze class distributions and imbalances, explore embedding space and data gaps, find near/exact duplicates, create curated subsets using semantic search and brain ops, build train/val/test splits, and answer natural language questions about your data. Delegates to fiftyone-find-duplicates and fiftyone-embeddings-visualization. Requires FiftyOne MCP server with @voxel51/brain and @voxel51/utils plugins.
1 skill
Export FiftyOne datasets to standard formats (COCO, YOLO, VOC, CVAT, CSV, etc.) and Hugging Face Hub. Use when converting datasets, exporting for training, creating archives, sharing data in specific formats, or publishing datasets to Hugging Face Hub.
1 skill
RuVLLM local inference with chat formatting, MicroLoRA fine-tuning, and SONA adaptation
3 skills · 1 command · 1 agent
Build high-quality datasets and computer vision models. Visualize datasets, analyze models, find duplicates, run inference, evaluate predictions, and develop custom plugins.
18 skills · 2 commands · 1 MCP server
Answer questions about past agent runs from the recording, not from memory. Three read-only stdlib scripts over the session transcripts Claude Code and Codex already write: a finder that locates the run by repo, time window, touched file or command text; a timeline that numbers every step with its exit code, lists every file changed (flagging changes the agent never mentioned) and walks back from any step with each causal edge labelled recorded or inferred by a named rule; and a claim checker that tests a summary's claims (ran, passed, edited, not-edited, read) against the run and catches tests that passed before a later edit and exit codes that belong to the last command of a pipe. Secrets are always redacted. A UserPromptSubmit hook gives the agent this session's transcript path when a prompt asks about past work. Ships cs-run-forensics agent, /cs-run-forensics and /cs-check-claims commands and 3 cited references.
1 skill · 2 commands · 1 agent · hooks
Production LLM inference including vLLM, TensorRT-LLM, llama.cpp, and SGLang. Use when deploying models for production inference.
98 skills
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations (Claude Code Action, Gemini CLI, OpenAI Codex, GitHub AI Inference)
1 skill
Skills for MLX-VLM: command-line and server inference, convert/quantize, adding new models, benchmarking, contributing, cached-model listing, and reproducible GitHub issues.
8 skills
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