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 manhvann/codexkit --skill ai-multimodalgit clone --depth 1 https://github.com/manhvann/codexkitWrote 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/manhvann/codexkit/ai-multimodal)<a href="https://agentmods.dev/skills/manhvann/codexkit/ai-multimodal"><img src="https://agentmods.dev/badge/skills/manhvann/codexkit/ai-multimodal/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/manhvann/codexkit/ai-multimodal"><img src="https://agentmods.dev/badge/skills/manhvann/codexkit/ai-multimodal.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 | $0.00052 | $0.01639 |
| Opus 5.5 | $0.00021 | $0.00656 |
| Sonnet 5.5 | $0.00010 | $0.00328 |
| Haiku 4.5 | $0.00005 | $0.00164 |
Grade A, and why
ck:ai-multimodal 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Multimodal
Process audio, images, videos, documents, and generate images/videos using Google Gemini's multimodal API.
Setup
export GEMINI_API_KEY="your-key" # Get from https://aistudio.google.com/apikey
pip install google-genai python-dotenv pillow
API Key Rotation (Optional)
For high-volume usage or when hitting rate limits, configure multiple API keys:
# Primary key (required)
export GEMINI_API_KEY="key1"
# Additional keys for rotation (optional)
export GEMINI_API_KEY_2="key2"
export GEMINI_API_KEY_3="key3"
Or in your .env file:
GEMINI_API_KEY=key1
GEMINI_API_KEY_2=key2
GEMINI_API_KEY_3=key3
Features:
- Auto-rotates on rate limit (429/RESOURCE_EXHAUSTED) errors
- 60-second cooldown per key after rate limit
- Logs rotation events with
--verboseflag - Backward compatible: single key still works
Quick Start
Verify setup: python scripts/check_setup.py
Analyze media: python scripts/gemini_batch_process.py --files <file> --task <analyze|transcribe|extract>
- TIP: When you're asked to analyze an image, check if
geminicommand is available, then useecho "<prompt to analyze image>" | gemini -y -m <gemini.model>command (read model from.codex/.ck.json:gemini.model). Ifgeminicommand is not available, usepython scripts/gemini_batch_process.py --files <file> --task analyzecommand. Generate content:python scripts/gemini_batch_process.py --task <generate|generate-video> --prompt "description"
Stdin support: You can pipe files directly via stdin (auto-detects PNG/JPG/PDF/WAV/MP3).
cat image.png | python scripts/gemini_batch_process.py --task analyze --prompt "Describe this"python scripts/gemini_batch_process.py --files image.png --task analyze(traditional)
Models
- Image generation:
imagen-4.0-generate-001(standard),imagen-4.0-ultra-generate-001(quality),imagen-4.0-fast-generate-001(speed) - Video generation:
veo-3.1-generate-preview(8s clips with audio) - Analysis:
gemini-2.5-flash(recommended),gemini-2.5-pro(advanced)
What ships with it
16 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.
- .env.example 8.1 KB
- references/audio-processing.md 9.9 KB
- references/image-generation.md 26 KB
- references/music-generation.md 8.8 KB
- references/video-analysis.md 12 KB
- references/video-generation.md 11 KB
- references/vision-understanding.md 11 KB
- scripts/check_setup.py 9.4 KB runs code
- scripts/document_converter.py 12 KB runs code
- scripts/gemini_batch_process.py 43 KB runs code
- scripts/media_optimizer.py 16 KB runs code
- scripts/requirements.txt 442 B
- scripts/tests/requirements.txt 352 B
- scripts/tests/test_document_converter.py 2.2 KB runs code
- scripts/tests/test_gemini_batch_process.py 12 KB runs code
- scripts/tests/test_media_optimizer.py 12 KB runs code
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 First seen · 111 lines · 52 tokens per session scan A 9d7f04a4fab2
ck:ai-multimodal is a skill published in the GitHub repository manhvann/codexkit (89 stars, last pushed 1mo ago), licensed MIT. It adds 52 tokens to every session and 1,639 once invoked, about $0.0002 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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