gemini-video-understanding

Original：🇺🇸 English

Translated

Analyze videos using Google's Gemini API - describe content, answer questions, transcribe audio with visual descriptions, reference timestamps, clip videos, and process YouTube URLs. Supports 9 video formats, multiple models (Gemini 2.5/2.0), and context windows up to 2M tokens (6 hours of video).

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Sourceaia-11-hn-mib/mib-mockinterviewaibot

Added on2026-02-20

NPX Install

npx skill4agent add aia-11-hn-mib/mib-mockinterviewaibot gemini-video-understanding

SKILL.md Content

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Gemini Video Understanding Skill

This skill enables comprehensive video analysis using Google's Gemini API, including video summarization, question answering, transcription, timestamp references, and more.

Capabilities

Video Summarization: Create concise summaries of video content
Question Answering: Answer specific questions about video content
Transcription: Transcribe audio with visual descriptions and timestamps
Timestamp References: Query specific moments in videos (MM:SS format)
Video Clipping: Process specific segments using start/end offsets
Multiple Videos: Compare and analyze up to 10 videos (Gemini 2.5+)
YouTube Support: Analyze YouTube videos directly (preview feature)
Custom Frame Rate: Adjust FPS sampling for different video types

Supported Formats

MP4, MPEG, MOV, AVI, FLV, MPG, WebM, WMV, 3GPP

Models Available

Gemini 2.5 Series:

```
gemini-2.5-pro
```
- Best quality, 1M context
```
gemini-2.5-flash
```
- Balanced quality/speed, 1M context
```
gemini-2.5-flash-preview-09-2025
```
- Preview features, 1M context

Gemini 2.0 Series:

```
gemini-2.0-flash
```
- Fast processing
```
gemini-2.0-flash-lite
```
- Lightweight option

Context Windows:

2M token models: ~2 hours (default) or ~6 hours (low-res)
1M token models: ~1 hour (default) or ~3 hours (low-res)

API Key Configuration

The skill supports both Google AI Studio and Vertex AI endpoints.

Option 1: Google AI Studio (Default)

The skill checks for

GEMINI_API_KEY

in this order:

Process environment:

process.env.GEMINI_API_KEY

$GEMINI_API_KEY

Project root:
```
.env
```
.claude directory:
```
.claude/.env
```
.claude/skills directory:
```
.claude/skills/.env
```

Skill directory:

.claude/skills/gemini-video-understanding/.env

Get your API key: https://aistudio.google.com/apikey

To set up:

bash

# Environment variable (recommended)
export GEMINI_API_KEY="your-api-key-here"

# Or in .env file
echo "GEMINI_API_KEY=your-api-key-here" > .env

Option 2: Vertex AI

To use Vertex AI instead:

bash

# Enable Vertex AI
export GEMINI_USE_VERTEX=true
export VERTEX_PROJECT_ID=your-gcp-project-id
export VERTEX_LOCATION=us-central1  # Optional, defaults to us-central1

Or in

.env

file:

bash

GEMINI_USE_VERTEX=true
VERTEX_PROJECT_ID=your-gcp-project-id
VERTEX_LOCATION=us-central1

Usage Instructions

When to Use This Skill

Use this skill when the user asks to:

Analyze, summarize, or describe video content
Answer questions about videos
Transcribe video audio with visual context
Extract information from specific timestamps
Compare multiple videos
Process YouTube video content
Create quizzes or educational content from videos

Basic Video Analysis

For video files:

python

python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --video-path "/path/to/video.mp4" \
  --prompt "Summarize this video in 3 key points"

For YouTube URLs:

python

python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --youtube-url "https://www.youtube.com/watch?v=VIDEO_ID" \
  --prompt "What are the main topics discussed?"

Advanced Features

Video Clipping (specific time range):

python

python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --video-path "/path/to/video.mp4" \
  --prompt "Summarize this segment" \
  --start-offset "40s" \
  --end-offset "80s"

Custom Frame Rate:

python

python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --video-path "/path/to/video.mp4" \
  --prompt "Analyze the rapid movements" \
  --fps 5

Transcription with Timestamps:

python

python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --video-path "/path/to/video.mp4" \
  --prompt "Transcribe the audio with timestamps and visual descriptions"

Multiple Videos (Gemini 2.5+ only):

python

python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --video-paths "/path/video1.mp4" "/path/video2.mp4" \
  --prompt "Compare these two videos and highlight the differences"

Model Selection:

python

python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --video-path "/path/to/video.mp4" \
  --prompt "Detailed analysis" \
  --model "gemini-2.5-pro"

Script Parameters

Required (one of):
  --video-path PATH           Path to local video file
  --youtube-url URL           YouTube video URL
  --video-paths PATH [PATH..] Multiple video paths (Gemini 2.5+)

Required:
  --prompt TEXT              Analysis prompt/question

Optional:
  --model NAME               Model to use (default: gemini-2.5-flash)
  --start-offset TIME        Video clip start (e.g., "40s", "1m30s")
  --end-offset TIME          Video clip end (e.g., "80s", "2m")
  --fps NUMBER               Frame sampling rate (default: 1)
  --output-file PATH         Save response to file
  --verbose                  Show detailed processing info

Common Use Cases

1. Video Summarization

Prompt: "Summarize this video in 3 key points with timestamps"

2. Educational Content

Prompt: "Create a quiz with 5 questions and answer key based on this video"

3. Timestamp-Specific Questions

Prompt: "What happens at 01:15 and how does it relate to the topic at 02:30?"

4. Transcription

Prompt: "Transcribe the audio from this video with timestamps for salient events and visual descriptions"

5. Content Comparison

Prompt: "Compare these two product demo videos. Which one explains the features more clearly?"

6. Action Detection

Prompt: "List all the actions performed in this tutorial video with timestamps"

Rate Limits & Quotas

Free Tier (per model):

10-15 RPM (requests per minute)
1M-4M TPM (tokens per minute)
1,500 RPD (requests per day)

YouTube Limitations:

Free tier: 8 hours of YouTube video per day
Paid tier: No length-based limits
Public videos only (no private/unlisted)

Storage (Files API):

20GB per project
2GB per file
48-hour retention period

Token Calculation

Video tokens depend on resolution:

Default resolution: ~300 tokens per second of video
Low resolution: ~100 tokens per second of video

Example: A 10-minute video = 600 seconds × 300 tokens = ~180,000 tokens

Error Handling

Common errors and solutions:

Error	Cause	Solution
400 Bad Request	Invalid video format or corrupt file	Check file format and integrity
403 Forbidden	Invalid/missing API key	Verify GEMINI_API_KEY configuration
404 Not Found	File URI not found	Ensure file is uploaded and active
429 Too Many Requests	Rate limit exceeded	Implement backoff, upgrade to paid tier
500 Internal Error	Server-side issue	Retry with exponential backoff

Best Practices

Use Files API for videos >20MB - More reliable than inline data
Wait for file processing - Poll until state is ACTIVE before analysis
Optimize FPS - Use lower FPS for static content to save tokens
Clip long videos - Process specific segments instead of entire video
Cache context - Reuse uploaded files for multiple queries
Batch processing - Process multiple short videos in one request (2.5+)
Specific prompts - Be precise about what you want to extract

Implementation Notes

For Claude Code:

When a user requests video analysis:

Check API key availability first using the helper script
Determine video source: local file, YouTube URL, or multiple videos
Select appropriate model based on requirements (default: gemini-2.5-flash)
Run the analysis script with proper parameters
Parse and present results to the user clearly
Handle errors gracefully with helpful suggestions

Files API Workflow:

For videos >20MB or reusable content:

Upload video using Files API (script handles this automatically)
Wait for ACTIVE state (polling included in script)
Use file URI for analysis
Files auto-delete after 48 hours

Inline Data Workflow:

For videos <20MB:

Read video file as bytes
Base64 encode for API
Send in generateContent request
Single-use, no upload needed

Example Workflows

Workflow 1: YouTube Video Summary

bash

# User: "Analyze this YouTube tutorial video"
python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --youtube-url "https://www.youtube.com/watch?v=abc123" \
  --prompt "Create a structured summary with: 1) Main topics, 2) Key takeaways, 3) Recommended audience"

Workflow 2: Interview Transcription

bash

# User: "Transcribe this interview with timestamps"
python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --video-path "interview.mp4" \
  --prompt "Transcribe this interview with speaker labels, timestamps, and visual descriptions of gestures or slides shown"

Workflow 3: Product Comparison

bash

# User: "Compare these two product demo videos"
python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --video-paths "demo1.mp4" "demo2.mp4" \
  --model "gemini-2.5-pro" \
  --prompt "Compare these product demos on: features shown, presentation quality, clarity of explanation, and overall effectiveness"

Troubleshooting

API Key Not Found:

bash

# Check API key detection
python .claude/skills/gemini-video-understanding/scripts/check_api_key.py

Video Too Large:

Error: Request size exceeds 20MB
Solution: Script automatically uses Files API for large videos

Processing Timeout:

Error: File not reaching ACTIVE state
Solution: Check video integrity, try smaller file, or different format

Rate Limit Errors:

Error: 429 Too Many Requests
Solution: Wait before retry, or upgrade to paid tier

Additional Resources

API Documentation: https://ai.google.dev/gemini-api/docs/video-understanding
Files API Guide: https://ai.google.dev/gemini-api/docs/vision#uploading-files
Rate Limits: https://ai.google.dev/gemini-api/docs/rate-limits
Pricing: https://ai.google.dev/pricing
Get API Key: https://aistudio.google.com/apikey

Version History

1.0.0 (2025-10-26): Initial release with full video understanding capabilities

Gemini Video Understanding Skill

This skill enables comprehensive video analysis using Google's Gemini API, including video summarization, question answering, transcription, timestamp references, and more.

Capabilities

Video Summarization: Create concise summaries of video content
Question Answering: Answer specific questions about video content
Transcription: Transcribe audio with visual descriptions and timestamps
Timestamp References: Query specific moments in videos (MM:SS format)
Video Clipping: Process specific segments using start/end offsets
Multiple Videos: Compare and analyze up to 10 videos (Gemini 2.5+)
YouTube Support: Analyze YouTube videos directly (preview feature)
Custom Frame Rate: Adjust FPS sampling for different video types

Supported Formats

MP4, MPEG, MOV, AVI, FLV, MPG, WebM, WMV, 3GPP

Models Available

Gemini 2.5 Series:

```
gemini-2.5-pro
```
- Best quality, 1M context
```
gemini-2.5-flash
```
- Balanced quality/speed, 1M context
```
gemini-2.5-flash-preview-09-2025
```
- Preview features, 1M context

Gemini 2.0 Series:

```
gemini-2.0-flash
```
- Fast processing
```
gemini-2.0-flash-lite
```
- Lightweight option

Context Windows:

2M token models: ~2 hours (default) or ~6 hours (low-res)
1M token models: ~1 hour (default) or ~3 hours (low-res)

API Key Configuration

The skill supports both Google AI Studio and Vertex AI endpoints.

Option 1: Google AI Studio (Default)

The skill checks for

GEMINI_API_KEY

in this order:

Process environment:

process.env.GEMINI_API_KEY

$GEMINI_API_KEY

Project root:
```
.env
```
.claude directory:
```
.claude/.env
```
.claude/skills directory:
```
.claude/skills/.env
```

Skill directory:

.claude/skills/gemini-video-understanding/.env

Get your API key: https://aistudio.google.com/apikey

To set up:

bash

# Environment variable (recommended)
export GEMINI_API_KEY="your-api-key-here"

# Or in .env file
echo "GEMINI_API_KEY=your-api-key-here" > .env

Option 2: Vertex AI

To use Vertex AI instead:

bash

# Enable Vertex AI
export GEMINI_USE_VERTEX=true
export VERTEX_PROJECT_ID=your-gcp-project-id
export VERTEX_LOCATION=us-central1  # Optional, defaults to us-central1

Or in

.env

file:

bash

GEMINI_USE_VERTEX=true
VERTEX_PROJECT_ID=your-gcp-project-id
VERTEX_LOCATION=us-central1

Usage Instructions

When to Use This Skill

Use this skill when the user asks to:

Analyze, summarize, or describe video content
Answer questions about videos
Transcribe video audio with visual context
Extract information from specific timestamps
Compare multiple videos
Process YouTube video content
Create quizzes or educational content from videos

Basic Video Analysis

For video files:

python

python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --video-path "/path/to/video.mp4" \
  --prompt "Summarize this video in 3 key points"

For YouTube URLs:

python

python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --youtube-url "https://www.youtube.com/watch?v=VIDEO_ID" \
  --prompt "What are the main topics discussed?"

Advanced Features

Video Clipping (specific time range):

python

python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --video-path "/path/to/video.mp4" \
  --prompt "Summarize this segment" \
  --start-offset "40s" \
  --end-offset "80s"

Custom Frame Rate:

python

python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --video-path "/path/to/video.mp4" \
  --prompt "Analyze the rapid movements" \
  --fps 5

Transcription with Timestamps:

python

python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --video-path "/path/to/video.mp4" \
  --prompt "Transcribe the audio with timestamps and visual descriptions"

Multiple Videos (Gemini 2.5+ only):

python

python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --video-paths "/path/video1.mp4" "/path/video2.mp4" \
  --prompt "Compare these two videos and highlight the differences"

Model Selection:

python

python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --video-path "/path/to/video.mp4" \
  --prompt "Detailed analysis" \
  --model "gemini-2.5-pro"

Script Parameters

Required (one of):
  --video-path PATH           Path to local video file
  --youtube-url URL           YouTube video URL
  --video-paths PATH [PATH..] Multiple video paths (Gemini 2.5+)

Required:
  --prompt TEXT              Analysis prompt/question

Optional:
  --model NAME               Model to use (default: gemini-2.5-flash)
  --start-offset TIME        Video clip start (e.g., "40s", "1m30s")
  --end-offset TIME          Video clip end (e.g., "80s", "2m")
  --fps NUMBER               Frame sampling rate (default: 1)
  --output-file PATH         Save response to file
  --verbose                  Show detailed processing info

Common Use Cases

1. Video Summarization

Prompt: "Summarize this video in 3 key points with timestamps"

2. Educational Content

Prompt: "Create a quiz with 5 questions and answer key based on this video"

3. Timestamp-Specific Questions

Prompt: "What happens at 01:15 and how does it relate to the topic at 02:30?"

4. Transcription

Prompt: "Transcribe the audio from this video with timestamps for salient events and visual descriptions"

5. Content Comparison

Prompt: "Compare these two product demo videos. Which one explains the features more clearly?"

6. Action Detection

Prompt: "List all the actions performed in this tutorial video with timestamps"

Rate Limits & Quotas

Free Tier (per model):

10-15 RPM (requests per minute)
1M-4M TPM (tokens per minute)
1,500 RPD (requests per day)

YouTube Limitations:

Free tier: 8 hours of YouTube video per day
Paid tier: No length-based limits
Public videos only (no private/unlisted)

Storage (Files API):

20GB per project
2GB per file
48-hour retention period

Token Calculation

Video tokens depend on resolution:

Default resolution: ~300 tokens per second of video
Low resolution: ~100 tokens per second of video

Example: A 10-minute video = 600 seconds × 300 tokens = ~180,000 tokens

Error Handling

Common errors and solutions:

Error	Cause	Solution
400 Bad Request	Invalid video format or corrupt file	Check file format and integrity
403 Forbidden	Invalid/missing API key	Verify GEMINI_API_KEY configuration
404 Not Found	File URI not found	Ensure file is uploaded and active
429 Too Many Requests	Rate limit exceeded	Implement backoff, upgrade to paid tier
500 Internal Error	Server-side issue	Retry with exponential backoff

Best Practices

Use Files API for videos >20MB - More reliable than inline data
Wait for file processing - Poll until state is ACTIVE before analysis
Optimize FPS - Use lower FPS for static content to save tokens
Clip long videos - Process specific segments instead of entire video
Cache context - Reuse uploaded files for multiple queries
Batch processing - Process multiple short videos in one request (2.5+)
Specific prompts - Be precise about what you want to extract

Implementation Notes

For Claude Code:

When a user requests video analysis:

Check API key availability first using the helper script
Determine video source: local file, YouTube URL, or multiple videos
Select appropriate model based on requirements (default: gemini-2.5-flash)
Run the analysis script with proper parameters
Parse and present results to the user clearly
Handle errors gracefully with helpful suggestions

Files API Workflow:

For videos >20MB or reusable content:

Upload video using Files API (script handles this automatically)
Wait for ACTIVE state (polling included in script)
Use file URI for analysis
Files auto-delete after 48 hours

Inline Data Workflow:

For videos <20MB:

Read video file as bytes
Base64 encode for API
Send in generateContent request
Single-use, no upload needed

Example Workflows

Workflow 1: YouTube Video Summary

bash

# User: "Analyze this YouTube tutorial video"
python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --youtube-url "https://www.youtube.com/watch?v=abc123" \
  --prompt "Create a structured summary with: 1) Main topics, 2) Key takeaways, 3) Recommended audience"

Workflow 2: Interview Transcription

bash

# User: "Transcribe this interview with timestamps"
python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --video-path "interview.mp4" \
  --prompt "Transcribe this interview with speaker labels, timestamps, and visual descriptions of gestures or slides shown"

Workflow 3: Product Comparison

bash

# User: "Compare these two product demo videos"
python .claude/skills/gemini-video-understanding/scripts/analyze_video.py \
  --video-paths "demo1.mp4" "demo2.mp4" \
  --model "gemini-2.5-pro" \
  --prompt "Compare these product demos on: features shown, presentation quality, clarity of explanation, and overall effectiveness"

Troubleshooting

API Key Not Found:

bash

# Check API key detection
python .claude/skills/gemini-video-understanding/scripts/check_api_key.py

Video Too Large:

Error: Request size exceeds 20MB
Solution: Script automatically uses Files API for large videos

Processing Timeout:

Error: File not reaching ACTIVE state
Solution: Check video integrity, try smaller file, or different format

Rate Limit Errors:

Error: 429 Too Many Requests
Solution: Wait before retry, or upgrade to paid tier

Additional Resources

API Documentation: https://ai.google.dev/gemini-api/docs/video-understanding
Files API Guide: https://ai.google.dev/gemini-api/docs/vision#uploading-files
Rate Limits: https://ai.google.dev/gemini-api/docs/rate-limits
Pricing: https://ai.google.dev/pricing
Get API Key: https://aistudio.google.com/apikey

Version History

1.0.0 (2025-10-26): Initial release with full video understanding capabilities

gemini-video-understanding

NPX Install

Tags

SKILL.md Content

Gemini Video Understanding Skill

Capabilities

Supported Formats

Models Available

API Key Configuration

Option 1: Google AI Studio (Default)

Option 2: Vertex AI

Usage Instructions

When to Use This Skill

Basic Video Analysis

Advanced Features

Script Parameters

Common Use Cases

1. Video Summarization

2. Educational Content

3. Timestamp-Specific Questions

4. Transcription

5. Content Comparison

6. Action Detection

Rate Limits & Quotas

Token Calculation

Error Handling

Best Practices

Implementation Notes

For Claude Code:

Files API Workflow:

Inline Data Workflow:

Example Workflows

Workflow 1: YouTube Video Summary

Workflow 2: Interview Transcription

Workflow 3: Product Comparison

Troubleshooting

Additional Resources

Version History

gemini-video-understanding

NPX Install

Tags

SKILL.md Content

Gemini Video Understanding Skill

Capabilities

Supported Formats

Models Available

API Key Configuration

Option 1: Google AI Studio (Default)

Option 2: Vertex AI

Usage Instructions

When to Use This Skill

Basic Video Analysis

Advanced Features

Script Parameters

Common Use Cases

1. Video Summarization

2. Educational Content

3. Timestamp-Specific Questions

4. Transcription

5. Content Comparison

6. Action Detection

Rate Limits & Quotas

Token Calculation

Error Handling

Best Practices

Implementation Notes

For Claude Code:

Files API Workflow:

Inline Data Workflow:

Example Workflows

Workflow 1: YouTube Video Summary

Workflow 2: Interview Transcription

Workflow 3: Product Comparison

Troubleshooting

Additional Resources

Version History