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 kyh/vibedgames --skill model-promptinggit clone --depth 1 https://github.com/kyh/vibedgamesWrote 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/kyh/vibedgames/model-prompting)<a href="https://agentmods.dev/skills/kyh/vibedgames/model-prompting"><img src="https://agentmods.dev/badge/skills/kyh/vibedgames/model-prompting.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Prompt Injection · line 14 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
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 | $0.00104 | $0.00642 |
| Opus 5 | $0.00052 | $0.00321 |
| Sonnet 5 | $0.00021 | $0.00128 |
| Haiku 4.5 | $0.00010 | $0.00064 |
Grade A, and why
model-prompting 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 9d 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 — 35 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Model Prompting
Runtime: All endpoint calls use the
vg generateCLI (npm install -g vibedgames, orpnpm dogfoodin this repo). The API key lives on the vibedgames server, so there is no per-machine setup. See thegenerateskill for the command reference.
Model families have meaningful prompting nuances. A prompt that works on GPT Image 2 (long, structured, exact text in quotes) will fail on Happy Horse (which wants ~20 plain-English words). This skill collects family-specific guides.
When to load which reference
| Reference | Load when |
|---|---|
| kling.md | Working with Kling video models (O3, v3), multi-prompt, element controls, Standard vs Pro tier |
| gpt-image-2.md | Working with openai/gpt-image-2 or /edit, structured prompts, EXACT TEXT, multi-image compositing |
| happy-horse.md | Working with alibaba/happy-horse/text-to-video or image-to-video, brevity-first, camera language |
Universal principles (all families)
- Visual facts beat prestige adjectives. Replace "stunning, cinematic, masterpiece" with "overcast daylight, brushed aluminum, 50mm feel."
- Style tags need visual targets. "Minimalist brutalist" → "cream background, heavy black sans serif, asymmetrical type block, generous negative space."
- One controlled variable per iteration. Comparison only works when one axis changes at a time.
- Inspect schema before assuming a control exists.
vg generate schema <endpoint_id> --json. Negative prompt, seed, multi-prompt, and reference-image fields differ across families. - Per-family rules override universal advice. Happy Horse rejects what GPT Image 2 rewards.
What ships with it
3 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.
- 9d ago First seen · 35 lines · 104 tokens per session scan A 799cec4a26e6
model-prompting is a skill published in the GitHub repository kyh/vibedgames (55 stars, last pushed today), licensed MIT. It adds 104 tokens to every session and 642 once invoked, about $0.0005 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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