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 nevergoodstudy-hub/wechat-article-summarizer --skill ai-multimodalgit clone --depth 1 https://github.com/nevergoodstudy-hub/wechat-article-summarizerWrote 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/nevergoodstudy-hub/wechat-article-summarizer/ai-multimodal)<a href="https://agentmods.dev/skills/nevergoodstudy-hub/wechat-article-summarizer/ai-multimodal"><img src="https://agentmods.dev/badge/skills/nevergoodstudy-hub/wechat-article-summarizer/ai-multimodal.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00175 | $0.02843 |
| Opus 5 | $0.00088 | $0.01422 |
| Sonnet 5 | $0.00035 | $0.00569 |
| Haiku 4.5 | $0.00017 | $0.00284 |
Grade B, and why
ai-multimodal scanned grade B with 1 finding 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 8d 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.
Unrestricted tool accessmediumExcessive agency
A wildcard tool grant or "run any command" leaves no least-privilege boundary at all.
Run any script with `--help` for detailed usage. This is a copy
100% identical to ai-multimodal — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 358 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Multimodal Processing Skill
Process audio, images, videos, documents, and generate images using Google Gemini's multimodal API. Unified interface for all multimedia content understanding and generation.
Core Capabilities
Audio Processing
- Transcription with timestamps (up to 9.5 hours)
- Audio summarization and analysis
- Speech understanding and speaker identification
- Music and environmental sound analysis
- Text-to-speech generation with controllable voice
Image Understanding
- Image captioning and description
- Object detection with bounding boxes (2.0+)
- Pixel-level segmentation (2.5+)
- Visual question answering
- Multi-image comparison (up to 3,600 images)
- OCR and text extraction
Video Analysis
- Scene detection and summarization
- Video Q&A with temporal understanding
- Transcription with visual descriptions
- YouTube URL support
- Long video processing (up to 6 hours)
- Frame-level analysis
Document Extraction
- Native PDF vision processing (up to 1,000 pages)
- Table and form extraction
- Chart and diagram analysis
- Multi-page document understanding
- Structured data output (JSON schema)
- Format conversion (PDF to HTML/JSON)
Image Generation
- Text-to-image generation
- Image editing and modification
- Multi-image composition (up to 3 images)
- Iterative refinement
- Multiple aspect ratios (1:1, 16:9, 9:16, 4:3, 3:4)
- Controllable style and quality
Capability Matrix
| Task | Audio | Image | Video | Document | Generation |
|---|---|---|---|---|---|
| Transcription | ✓ | - | ✓ | - | - |
| Summarization | ✓ | ✓ | ✓ | ✓ | - |
| Q&A | ✓ | ✓ | ✓ | ✓ | - |
| Object Detection | - | ✓ | ✓ | - | - |
| Text Extraction | - | ✓ | - | ✓ | - |
| Structured Output | ✓ | ✓ | ✓ | ✓ | - |
| Creation | TTS | - | - | - | ✓ |
| Timestamps | ✓ | - | ✓ | - | - |
| Segmentation | - | ✓ | - | - | - |
Model Selection Guide
Gemini 2.5 Series (Recommended)
- gemini-2.5-pro: Highest quality, all features, 1M-2M context
- gemini-2.5-flash: Best balance, all features, 1M-2M context
- gemini-2.5-flash-lite: Lightweight, segmentation support
- gemini-2.5-flash-image: Image generation only
What ships with it
13 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 4.2 KB
- references/audio-processing.md 9.2 KB
- references/image-generation.md 13 KB
- references/video-analysis.md 11 KB
- references/vision-understanding.md 11 KB
- scripts/document_converter.py 12 KB runs code
- scripts/gemini_batch_process.py 17 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 9.6 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.
- 8d ago First seen · 358 lines · 175 tokens per session scan B 492e291734b1
ai-multimodal is a skill published in the GitHub repository nevergoodstudy-hub/wechat-article-summarizer (5 stars, last pushed 2mo ago), licensed MIT. It adds 175 tokens to every session and 2,843 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it B with 1 finding (unrestricted tool access). It is 100% identical to ai-multimodal, differing in 0 lines, and is treated as a copy.
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