P ImageSAFE
inference.sh Agent skills for using our API to give your agents access to hundreds of apps and other agents
Overview
inference.sh Agent skills for using our API to give your agents access to hundreds of apps and other agents
d30242fc0e10OBSERVED · 2026-10-14Install
Commands as the repository documents them. They are shown, not run.
npx skills add inference-sh/skills@infsh-cli
npx skills add inference-sh/skills@ai-image-generation
npx skills add inference-sh/skills@p-video
npx skills add inference-sh/skills@flux-image
What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
---
name: p-image
description: "Generate images with Pruna P-Image models via inference.sh CLI. Models: P-Image, P-Image-LoRA, P-Image-Edit, P-Image-Edit-LoRA. Capabilities: text-to-image, image editing, LoRA styles, multi-image compositing, fast inference. Pruna optimizes models for speed without quality loss. Triggers: pruna, p-image, pruna image, fast image generation, optimized flux, pruna ai, p image, fast ai image, economic image generation, cheap image generation"
allowed-tools: Bash(belt *)
---
> **Install the belt CLI skill:** `npx skills add belt-sh/cli`
# Pruna P-Image Generation
Generate images with Pruna's optimized P-Image models via [inference.sh](https://inference.sh) CLI.

## Quick Start
> Requires inference.sh CLI (`belt`). [Install instructions](https://raw.githubusercontent.com/inference-sh/skills/refs/heads/main/cli-install.md)
```bash
belt login
belt app run pruna/p-image --input '{"prompt": "a futuristic cityscape at sunset"}'
```
## P-Image Models
Pruna optimizes AI models for speed without sacrificing quality.
| Model | App ID | Best For |
|-------|--------|----------|
| P-Image | `pruna/p-image` | Fast text-to-image, multiple aspect ratios |
| P-Image-LoRA | `pruna/p-image-lora` | Custom styles with preset LoRAs |
| P-Image-Edit | `pruna/p-image-edit` | Image editing with multi-image support |
| P-Image-Edit-LoRA | `pruna/p-image-edit-lora` | Stylized image editing |
## Examples
### Text-to-Image
```bash
belt app run pruna/p-image --input '{
"prompt": "professional product photo of sneakers, studio lighting",
"aspect_ratio": "1:1"
}'
```
### With LoRA Presets
P-Image-LoRA includes built-in style presets:
```bash
belt app run pruna/p-image-lora --input '{
"prompt": "portrait of a woman in golden hour light",
"lora_preset": "photos-realism"
}'
```
Available presets: `photos-realism`, `pixel-art`, `japanese-modern-look`, `cinematic-movie-style`, `graffiti-splash`, `neon-punk`, `anime-2-5d`, `ethereal-portrait`, `retro-90s-style`, `ink-sketchbook`, `paper-cut`
### Image Editing
```bash
belt app run pruna/p-image-edit --input '{
"prompt": "change the background to a beach",
"images": ["https://your-image.jpg"]
}'
```
### Multi-Image Compositing
```bash
belt app run pruna/p-image-edit --input '{
"prompt": "combine these images into a collage",
"images": ["https://img1.jpg", "https://img2.jpg", "https://img3.jpg"]
}'
```
### Custom Aspect Ratios
```bash
belt app run pruna/p-image --input '{
"prompt": "landscape mountain scene",
"aspect_ratio": "16:9"
}'
```
Supported ratios: `1:1`, `16:9`, `9:16`, `4:3`, `3:4`, `3:2`, `2:3`, or `custom` with width/height
## Other Pruna Models
Pruna offers optimized versions of popular models:
```bash
# FLUX Dev (optimized)
belt app run pruna/flux-dev --input '{"prompt": "..."}'
# FLUX Klein 4B (extremely fast, $0.0001/image)
belt app run pruna/flux-2-klein-4b --input '{"prompt": "..."}'
# Qwen Image
belt app run pruna/qwen-image --input '{"prompt": "..."}'
# Z-Image Turbo (ultra-fast)
belt app run pruna/z-image-turbo --input '{"prompt": "..."}'
# WAN Image Small (batch generation)
belt app run pruna/wan-image-small --input '{"prompt": "..."}'
```
## Browse All Pruna Apps
```bash
belt app list --namespace pruna
```
## Related Skills
```bash
# Full platform skill (all apps)
npx skills add inference-sh/skills@infsh-cli
# All image generation models
npx skills add inference-sh/skills@ai-image-generation
# Pruna video generation
npx skills add inference-sh/skills@p-video
# FLUX models
npx skills add inference-sh/skills@flux-image
```
Browse all apps: `belt app list`
## Documentation
- [Running Apps](https://inference.sh/docs/apps/running) - How to run apps via CLI
- [Image Generation Example](https://inference.sh/docs/examples/image-generation) - Complete image generation guide
- [Streaming Results](https://inference.sh/docs/api/sdk/streaming) - Real-time progress updatesTrust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (1)
Gates applied: no_behavioural_pass, no_license.
d30242fc0e10full audit observations/trust-audit/skill/inference-sh__p-image.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-14 | d30242fc0e10 | SAFE | B | 89 | first audit |
Questions
What does the P Image skill do?
inference.sh Agent skills for using our API to give your agents access to hundreds of apps and other agents
Is P Image safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can P Image access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (d30242fc0e10), read on 2026-10-14. The repository is watched, and a new audit runs when it changes — this is the first audit.