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-cataloggit 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-catalog)<a href="https://agentmods.dev/skills/kyh/vibedgames/model-catalog"><img src="https://agentmods.dev/badge/skills/kyh/vibedgames/model-catalog/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/kyh/vibedgames/model-catalog"><img src="https://agentmods.dev/badge/skills/kyh/vibedgames/model-catalog.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 | $0.00029 | $0.00650 |
| Opus 5.5 | $0.00012 | $0.00260 |
| Sonnet 5.5 | $0.00006 | $0.00130 |
| Haiku 4.5 | $0.00003 | $0.00065 |
Grade A, and why
model-catalog 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.
How it starts
The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Models Catalog
Endpoint-first navigation for production work. Each modality reference lists curated picks organized by use case (premium realism / fast & cheap / 4K / specialized). Before reaching for free-text search, consult the modality reference that matches the task.
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.
Endpoint-first rule
- Pick the endpoint ID from the right modality reference.
- Verify it:
vg generate models --endpoint_id <endpoint_id> --json. - Inspect it:
vg generate schema <endpoint_id> --json. - Check cost when relevant:
vg generate pricing <endpoint_id> --json. - Use text search only if the routed endpoint is missing, deprecated, rejected, or the role is not covered here:
vg generate models "<task description>" --json
vg generate docs "<topic>" --json
Do not invent endpoint IDs.
Modality references
Load the reference matching the user's task:
- text-to-image.md, image generation from prompt (text-heavy, premium still, fast draft)
- image-to-image.md, image editing, inpainting, background removal, upscaling
- text-to-video.md, video generation from prompt (highest quality, fast/economical, multi-shot storytelling)
- image-to-video.md, video from a reference frame (including audio-driven and lip-sync variants)
- video-to-video.md, video edit, restyle, upscale, background removal
- text-to-3d.md, 3D model generation from text
- image-to-3d.md, 3D model generation from reference images
- text-to-audio.md. TTS, music, SFX generation
- audio-to-text.md, speech-to-text (Whisper, ElevenLabs Scribe with diarization)
- image-to-text.md. OCR, captioning, VQA, detection, segmentation
- campaign-ugc.md, use-case routing for marketing campaign assets and creator/UGC ads
What ships with it
11 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.
- references/audio-to-text.md 1.8 KB
- references/campaign-ugc.md 1.3 KB
- references/image-to-3d.md 3.4 KB
- references/image-to-image.md 4.5 KB
- references/image-to-text.md 2.8 KB
- references/image-to-video.md 4.7 KB
- references/text-to-3d.md 1.9 KB
- references/text-to-audio.md 3.0 KB
- references/text-to-image.md 4.3 KB
- references/text-to-video.md 2.2 KB
- references/video-to-video.md 2.7 KB
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 Changed · -86 tokens per session d4c176cd2257
- 1mo ago First seen · 48 lines · 115 tokens per session scan A 67ad04e62ea1
model-catalog is a skill published in the GitHub repository kyh/vibedgames (60 stars, last pushed 3d ago), licensed MIT. It adds 29 tokens to every session and 650 once invoked, about $0.0001 per session on Opus 5.5. 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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