ck:ai-multimodal

ck:ai-multimodal is a skill for Claude Code from manhvann/codexkit. It costs 52 tokens per session (1,639 once invoked), scanned A, original, MIT.

A tool for analyzing images, audio, video, and documents through Google’s Gemini service, and for generating images with Imagen 4 or videos with Veo 3. It requires a Gemini API key and can process files from the command line.

In plain words
What is it for?
Use it to analyze media, transcribe recordings, extract text from documents or images, read image text with OCR, and create images or videos.
Why use it?
It gives a coding agent access to visual and audio information that text-only tools cannot inspect, including transcription, text extraction, and OCR. It can also rotate among configured API keys after rate-limit errors.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: installed under .agents/ (shared by several agents); mentions Codex.

Good fit Use it to analyze media, transcribe recordings, extract text from documents or images, read image text with OCR, and create images or videos.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/manhvann/codexkit/ai-multimodal
Install

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.

Any agent
npx skills add manhvann/codexkit --skill ai-multimodal
Clone the repo
git clone --depth 1 https://github.com/manhvann/codexkit

Made for: Claude Code.

Wrote 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.

agentmods badge for ck:ai-multimodal

README.md
[![agentmods](https://agentmods.dev/badge/skills/manhvann/codexkit/ai-multimodal/github.svg)](https://agentmods.dev/skills/manhvann/codexkit/ai-multimodal)
Your own site
<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.

agentmods 80×15 button for ck:ai-multimodal

Your own site · 80×15
<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>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,639 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 1mo ago against content hash 9d7f04a4fab2, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.

The scan reads SKILL.md. This mod also ships 7 executable files (scripts/check_setup.py, scripts/document_converter.py, scripts/gemini_batch_process.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.agents/skills/ai-multimodal/SKILL.md · 111 lines

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 --verbose flag
  • 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 gemini command is available, then use echo "<prompt to analyze image>" | gemini -y -m <gemini.model> command (read model from .codex/.ck.json: gemini.model). If gemini command is not available, use python scripts/gemini_batch_process.py --files <file> --task analyze command. 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)

Read the full file on GitHub · 111 lines

Changes

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.

  1. 1mo ago First seen · 111 lines · 52 tokens per session scan A 9d7f04a4fab2

Subscribe to this mod's changes

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.

Related

Other skills, from other repositories

agent-platform-model-registry

Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.

google/skills · 60 tokens

foundry-config-setup

Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.

microsoft/agent-framework · 65 tokens

google-cloud-solution-agentic-analytics-spark-knowledge-catalog

Discovers requirements and designs an end-to-end governed agentic analytics solution using Knowledge Catalog and Managed Service for Apache Spark (Lightning Engine). Use when designing data science and analytics workflows across structured and unstructured distributed data (including in S3, Azure Blob, AlloyDB, and…

google/skills · 132 tokens

training-check

Interactively monitor training metrics from the current Codex session, periodically checking WandB or fallback logs for NaN, divergence, plateaus, and broken runs.

wanshuiyin/Auto-claude-code-research-in-sleep · 35 tokens

nemo-automodel-launcher-config

Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.

NVIDIA/skills · 30 tokens

finetuning

Fine-tune models on Microsoft Foundry using SFT (supervised), DPO (preference), or RFT (reinforcement with graders). Covers dataset preparation, training job submission, deployment, and evaluation. USE FOR: fine-tune, SFT, DPO, RFT, training data, grader, distillation, fine-tuned model, training job, large file…

microsoft/skills · 132 tokens