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.
npx skills add Extelligence-ai/bagel --skill exporting-visualizationsgit clone --depth 1 https://github.com/Extelligence-ai/bagelWrote 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/skills/extelligence-ai/bagel/exporting-visualizations)<a href="https://agentmods.dev/skills/extelligence-ai/bagel/exporting-visualizations"><img src="https://agentmods.dev/badge/skills/extelligence-ai/bagel/exporting-visualizations/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/extelligence-ai/bagel/exporting-visualizations"><img src="https://agentmods.dev/badge/skills/extelligence-ai/bagel/exporting-visualizations.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00054 | $0.00256 |
| Opus 5 | $0.00027 | $0.00128 |
| Sonnet 5 | $0.00011 | $0.00051 |
| Haiku 4.5 | $0.00005 | $0.00026 |
Grade A, and why
exporting-visualizations 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 10d 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.
What it actually says
Exporting visualizations
Pick the target by what the user is doing, then call the matching bagel export tool:
| User goal | Target | Why first choice |
|---|---|---|
| Explore/replay multimodal data (3D, images, series) | Rerun (export_for_rerun) |
Best open-source robotics viewer |
| Web-based bag review, Foxglove-style | Lichtblick (export_for_lichtblick) |
Open-source; preferred over Foxglove |
| Plot signals from an artifact on the desktop | PlotJuggler (export_for_plotjuggler) |
Artifacts land on the host for it |
| Build a training dataset | LeRobot (export_for_lerobot) |
Direct dataset export |
Camera-topic GIFs for quick evidence come from the triage/pipeline workflows, not an export tool. Export artifacts land under the artifacts directory on the host — always report the output path.
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.
- 10d ago First seen · 21 lines · 54 tokens per session scan A c925dd70df83
exporting-visualizations is a skill published in the GitHub repository Extelligence-ai/bagel (397 stars, last pushed today), licensed Apache-2.0. It adds 54 tokens to every session and 256 once invoked, about $0.0003 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.
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