Borrowing it
Nothing to install: this file belongs to WayneJin0918/Omni-Rewriter. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/WayneJin0918/Omni-Rewriter/main/.cursor/skills/omni-rewriter-h3-pe/SKILL.mdgit clone --depth 1 https://github.com/WayneJin0918/Omni-RewriterWrote 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/waynejin0918/omni-rewriter/omni-rewriter-h3-pe)<a href="https://agentmods.dev/skills/waynejin0918/omni-rewriter/omni-rewriter-h3-pe"><img src="https://agentmods.dev/badge/skills/waynejin0918/omni-rewriter/omni-rewriter-h3-pe/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/waynejin0918/omni-rewriter/omni-rewriter-h3-pe"><img src="https://agentmods.dev/badge/skills/waynejin0918/omni-rewriter/omni-rewriter-h3-pe.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 | $0.00059 | $0.01293 |
| Opus 5 | $0.00030 | $0.00647 |
| Sonnet 5 | $0.00012 | $0.00259 |
| Haiku 4.5 | $0.00006 | $0.00129 |
Grade A, and why
omni-rewriter-h3-pe 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 13d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Omni-Rewriter PE skill
Mission
Omni-Rewriter is a model-extensible PE framework: transport-neutral intent → typed profile → deterministic validation/bounded repair → dialect render → optional explicit generation adapter. H3 and the initial image dialects are profiles, not framework limits. Prefer schema, validators, repairs, renderers, and public contracts over claims about private vendor internals.
Framework rules
- Expand is not generate. Expansion returns validated text/JSON; adapters and independent runners are opt-in consumers.
- A PE profile does not prove generation-runtime compatibility.
- Cite public runtime/API evidence, pin tested versions, and label untested paths unverified.
- Do not treat stock vLLM, model-specific vLLM forks, and vLLM-Omni as interchangeable.
- Preserve transport-neutral public contracts and keep model-specific mapping at profile/adapter boundaries.
When expanding video (Seedance)
- Set
metadata.video_pe_profile=seedance(default remains H3). - Support
t2va/ref2vaonly for this profile; requireduration_seconds. - Emit
SeedanceRewritefields: style, summary, static/dynamic descriptions, subjects, optionalreference_roles/stages/preserve/unused_materials, instruction, optional BGM,generate_audio. Follow public Seedance 2.5 habits (typed@Image/@Video/@Audio, role+exclude lines, observable stage end states,{dialogue}/<sfx>/(music)delimiters). Do not claim private vendor internals. - Render via
seedance_render=natural|fused|json(default natural = public 2.5 template) andseedance_ref_style=public|omni(default public type-local@Video 1). - Never commit private dump markers or vendor-internal corpus metadata. See
docs/dialects/seedance-pe.mdandassert_sanitized_seedance_payload. No generation adapter in this profile pass.
When expanding video (LTX-2.5)
- Set
metadata.video_pe_profile=ltx(default remains H3). - Support
t2va/i2va/l2va/fl2va/ref2va; requireduration_seconds. - Emit
LTXRewritefields that render to one flowing paragraph: action, movements, appearance, environment, camera, lighting, optional changes, audio whengenerate_audiois true. Follow the public LTX-2 guide (start with the action, ~200 words, no duration/resolution in the body). Image refs are generate-time--imageflags, not prompt tokens. - Render via
ltx_render=paragraph|json(default paragraph). OptionalLTXVideoRunnermaps the paragraph ontopython -m ltx_pipelines.distilled. Live generate is unverified. Seedocs/dialects/ltx-pe.md.
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.
- 13d ago First seen · 100 lines · 59 tokens per session scan A d12028a2c11b
omni-rewriter-h3-pe is a skill published in the GitHub repository WayneJin0918/Omni-Rewriter (85 stars, last pushed 23d ago), licensed Apache-2.0. It adds 59 tokens to every session and 1,293 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.
Other skills, from other repositories
seedance-prompt
This skill should be used when the user asks to write, improve, translate, compress, or debug a Seedance 2.0 video prompt; mentions T2V, I2V, V2V, R2V, camera direction, prompt quality, or provides reference assets for a production-ready prompt.
seedance-2-5-prompt-director
A skill for writing and improving prompts for Seedance 2.5, a video-generation system. It covers text-to-video, image-to-video, editing, video extension, references, camera movement, green-screen work, sound, and lip sync.
model-aware-image-prompt-engineer
Model-aware image prompt engineering for any agent or image generation workflow. Use when writing, improving, translating, debugging, or evaluating prompts for OpenAI image models, Gemini Nano Banana, Midjourney, FLUX, Qwen-Image, Z-Image, Stable Diffusion, SDXL, Pony, Illustrious, NoobAI, Animagine, HunyuanImage…
nano-banana-image-skill
Model-aware image prompting for Nano Banana Pro and Nano Banana 2. Covers generation, editing, continuity, text-in-image, style routing, and structured JSON output.
awesome-gpt-image-2
A structured library of reusable prompts for GPT-Image2, an image-generation model. It breaks prompts into parts such as subject, lighting, materials, composition, and visual details, with more than 20 templates.
mj-prompt
A prompt writer for Midjourney and niji, image-generation tools, using an East Asian visual style framework.