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 waybarrios/opencode-power-pack --skill huggingface-lora-space-buildergit clone --depth 1 https://github.com/waybarrios/opencode-power-packWrote 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/waybarrios/opencode-power-pack/huggingface-lora-space-builder)<a href="https://agentmods.dev/skills/waybarrios/opencode-power-pack/huggingface-lora-space-builder"><img src="https://agentmods.dev/badge/skills/waybarrios/opencode-power-pack/huggingface-lora-space-builder/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/waybarrios/opencode-power-pack/huggingface-lora-space-builder"><img src="https://agentmods.dev/badge/skills/waybarrios/opencode-power-pack/huggingface-lora-space-builder.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00053 | $0.07838 |
| Opus 5.5 | $0.00021 | $0.03135 |
| Sonnet 5.5 | $0.00011 | $0.01568 |
| Haiku 4.5 | $0.00005 | $0.00784 |
Grade A, and why
huggingface-lora-space-builder 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 1mo 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.
This is a copy
94% identical to huggingface-lora-space-builder — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 396 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gradio LoRA Space Builder
Build and publish a Gradio demo on Hugging Face Spaces that runs inference with a user-provided LoRA. Use whenever someone asks to create, generate, ship, or publish "a Space", "a demo", "a Gradio app", or "a playground" for a LoRA — whether the base model is Qwen-Image, Qwen-Image-Edit, LTX, or another diffusion model. Also use when someone describes a LoRA they trained or hosts on the Hub and wants to share it. The default target is ZeroGPU hardware and the default inference library is diffusers when the base model supports it.
The output is a real, published Space (private by default) that the user can try in the browser, not a local script.
What "good" looks like for these demos
The demo should feel handcrafted for this specific LoRA, not a generic template with the LoRA bolted on. Two LoRAs that share a task can still need different demos: a pose-control video LoRA and an outpainting video LoRA both take video in and produce video out, but the inputs the user provides, the preprocessing, and the controls are completely different. Recognizing that is the central job here.
Concretely, a good demo:
- Loads fast and runs fast — minimal model loading, sensible step count, no wasted computation per call.
- Has a UI with exactly the controls this LoRA needs and nothing else. Excess sliders are a cost, not a feature.
- Shows the user what's happening — progress, intermediate outputs where useful, the seed used, a clear error when input is missing.
- Honors the LoRA's own recommendations from its model card: trigger words, recommended step count, recommended guidance scale, recommended LoRA scale, example inputs.
- Is creative where creativity helps — interactive canvases, before/after sliders, side-by-side previews of intermediate processing — and plain where plainness is right.
Workflow
Work through these phases in order. Information gathered in one phase decides the next.
- Gather the LoRA info needed to pick a pipeline and design a UI.
- Pick the base pipeline and inference recipe.
- Design the UI for this specific LoRA's task and inputs.
- Write
app.py,requirements.txt, andREADME.mdtogether; show all three to the user for one batched approval. - Publish the Space (private).
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 396 lines · 53 tokens per session scan A 4573b1503007
huggingface-lora-space-builder is a skill published in the GitHub repository waybarrios/opencode-power-pack (544 stars, last pushed 5d ago), licensed MIT. It adds 53 tokens to every session and 7,838 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to huggingface-lora-space-builder, differing in 4 lines, and is treated as a copy.
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