voxel51-agent-setup

Answers FiftyOne Python SDK questions with accurate, runnable code. Use when the user asks how to do something in the FiftyOne Python SDK, asks a docs question, no skill or operator covers their goal, or the agent is unsure of the correct FiftyOne method, argument, or field path while writing code — e.g. "how do I do X in Python", "show me the SDK for filtering", "there's no operator for this, can I do it in code", "what's the API for embeddings", "write me a Python script to do Y".

Finds duplicate or near-duplicate images in FiftyOne datasets using brain similarity computation. Use when deduplicating datasets, finding similar images, or removing redundant samples.

Generate a Data Lens connector from an external database schema. Use when users want to connect an external data source (PostgreSQL, BigQuery, Databricks, MySQL, etc.) to FiftyOne Data Lens, or when they have a database schema and want to browse/import that data through the FiftyOne App.

Triages FiftyOne GitHub issues by categorizing as fixed, won't fix, not reproducible, or still valid. Use when reviewing GitHub issues, triaging bugs, or closing stale issues in the voxel51/fiftyone repository.

Evaluate model predictions against ground truth using COCO, Open Images, or custom protocols. Use when computing mAP, precision, recall, confusion matrices, or analyzing TP/FP/FN examples for detection, classification, segmentation, or regression tasks.

Build FiftyOne UIs using VOODO (@voxel51/voodo), the official React component library. Use when building plugin panels, creating interactive UIs, styling FiftyOne applications, or choosing components, text sizes, colors, and spacing. Looks up the installed version's components and token values with `npx @voxel51/voodo` before writing code.

Use when integrating a model into FiftyOne's remote model zoo — detection, classification, segmentation, embedding, keypoint, or vision-language (VLM) models loaded via `register_zoo_model_source` and `load_zoo_model`, then applied with `dataset.apply_model`. Also for debugging zoo registration, `manifest.json` issues, custom `fom.Model` / `TorchModelMixin` subclasses, DataLoader pickle errors, or worker `ModuleNotFoundError` from spawned DataLoader workers.

Evaluates FiftyOne plugins for quality, security, and agent-readiness. Use when reviewing a plugin before installation, auditing an existing plugin, validating a plugin you just built, or assessing community plugins for safety. Produces a structured report with scores and actionable recommendations.

Configure this repo for the engineering skills: set up its issue tracker, triage label vocabulary, and domain doc layout. Run once before first use of the other engineering skills.

Teach the user a new skill or concept, within this workspace.

Ask which skill or flow fits your situation. A router over the skills in this repo.

Plan a huge chunk of work (more than one agent session can hold) as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.

Hand the current conversation off to a fresh background agent that picks up the work immediately.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Use when starting any conversation - establishes how to find and use skills, requiring skill invocation before ANY response including clarifying questions

Use when executing implementation plans with independent tasks in the current session