Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/voxel51/fiftyone-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/voxel51/fiftyone-skills/help)<a href="https://agentmods.dev/commands/voxel51/fiftyone-skills/help"><img src="https://agentmods.dev/badge/commands/voxel51/fiftyone-skills/help.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00017 | $0.00864 |
| Opus 5 | $0.00009 | $0.00432 |
| Sonnet 5 | $0.00003 | $0.00173 |
| Haiku 4.5 | $0.00002 | $0.00086 |
Grade A, and why
help scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FiftyOne Skills Help
This plugin provides expert workflows for building high-quality datasets and computer vision models using FiftyOne.
When to Use This Help
- First time using FiftyOne skills
- Encountering setup or configuration issues
- Want to understand what skills are available
Prerequisites
Before using FiftyOne skills, ensure the MCP server is installed:
pip install fiftyone-mcp-server
The plugin automatically configures the MCP server connection via .mcp.json. If you installed FiftyOne in a virtual environment or conda environment, update the command path in .mcp.json to point to your environment's executable:
{
"mcpServers": {
"fiftyone": {
"command": "/path/to/your/venv/bin/fiftyone-mcp"
}
}
}
Available Skills
FiftyOne Use
Skills for working with datasets and models:
| Skill | Command | Use When |
|---|---|---|
| Dataset Import | /fiftyone:fiftyone-dataset-import |
Importing any dataset (COCO, YOLO, VOC, videos, point clouds, multimodal, Hugging Face Hub) |
| Dataset Export | /fiftyone:fiftyone-dataset-export |
Exporting datasets to standard formats or Hugging Face Hub for training or sharing |
| Find Duplicates | /fiftyone:fiftyone-find-duplicates |
Removing duplicate or near-duplicate images from datasets |
| Dataset Inference | /fiftyone:fiftyone-dataset-inference |
Running detection, classification, segmentation, or embeddings on data |
| Model Evaluation | /fiftyone:fiftyone-model-evaluation |
Computing mAP, precision, recall, confusion matrices |
| Embeddings Visualization | /fiftyone:fiftyone-embeddings-visualization |
Exploring dataset structure, finding clusters, identifying outliers |
| Create Notebook | /fiftyone:fiftyone-create-notebook |
Creating Jupyter notebooks for tutorials, getting-started guides, recipes, or ML pipelines |
FiftyOne Develop
Skills for developers building with FiftyOne:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 97 lines · 17 tokens per session scan A ce782ad41b80
help is a command published in the GitHub repository voxel51/fiftyone-skills (39 stars, last pushed 22d ago), licensed Apache-2.0. It adds 17 tokens to every session and 864 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.