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 perniemann/pnCore --skill pn-image-creatorgit clone --depth 1 https://github.com/perniemann/pnCoreWrote 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/perniemann/pncore/pn-image-creator)<a href="https://agentmods.dev/skills/perniemann/pncore/pn-image-creator"><img src="https://agentmods.dev/badge/skills/perniemann/pncore/pn-image-creator/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/perniemann/pncore/pn-image-creator"><img src="https://agentmods.dev/badge/skills/perniemann/pncore/pn-image-creator.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 | $0.00063 | $0.01027 |
| Opus 5 | $0.00032 | $0.00513 |
| Sonnet 5 | $0.00013 | $0.00205 |
| Haiku 4.5 | $0.00006 | $0.00103 |
Grade A, and why
pn-image-creator 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 6d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image create (workflow questionnaire)
When to use
- Invoked by workflow_step("image_create", ...) or get_command("pn-assets") (which routes to image_create).
- When the user wants a high-quality image (PNG, SVG) with content discussed before generation.
Required skills before specification (raster)
For PNG or any raster output: load get_skill('pn-cinematography-lighting') and get_skill('pn-image-prompt-engineering') at the start of the flow. Use them to shape the questionnaire answers and the final prompt: camera (framing, lens feel, depth), lighting (direction, quality, ratios, color temperature), style (medium, period, references). Do not generate until those dimensions are reflected in the agreed spec (user may shorten with explicit “use defaults” after you state the defaults you applied).
Questionnaire (ask explicitly; do not infer)
1. Subject and content
- What to depict: Subject, scene, or concept (e.g. hero image, product shot, illustration, diagram).
- Mood or message: Tone (e.g. professional, playful, minimal).
2. Environment, lighting, camera, and style
- Environment: Setting, background, context.
- Lighting: Motivated sources, hard vs soft, key-to-fill, color temperature—use pn-cinematography-lighting vocabulary; align shadow and highlight language with the described light.
- Camera: Shot size, angle, lens feel (e.g. wide vs portrait focal length), depth of field when relevant.
- Style: Photorealistic, flat illustration, 3D render, line art, era/film reference, etc.—tie to pn-image-prompt-engineering layered prompts.
3. Technical and output
- Format: PNG or SVG? (SVG → use pn-svg-creator skill for generation path.)
- Dimensions: For PNG: width × height (e.g. 1920×1080). For SVG: viewBox or size.
- Quality bar: Resolution, DPI if relevant, or "high-quality default."
4. Constraints
- A11y: Alt text or description for the asset?
- Output path: Default
assets/; user may specify.
What ships with it
1 file 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.
- 6d ago First seen · 70 lines · 63 tokens per session scan A 2bd7079eb3ca
pn-image-creator is a skill published in the GitHub repository perniemann/pnCore (0 stars, last pushed 3d ago), licensed MIT. It adds 63 tokens to every session and 1,027 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 2026-09-03.
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