gemini-batch
Process large volumes of requests using Gemini Batch API via scripts/. Use for batch processing, bulk text generation, processing JSONL files, async job execution, and cost-efficient high-volume AI tasks. Triggers on "batch processing", "bulk requests", "JSONL", "async job", "batch job".
npx skills add majiayu000/claude-skill-registry --skill gemini-batch-akrindev-google-studio-skills --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Gemini Batch Processing Process large volumes of requests efficiently using Gemini Batch API through executable scripts for cost savings and high throughput. ## When to Use This Skill Use this skill when you need to: - Process hundreds/thousands of requests - Generate content in bulk (blogs, emails, descriptions) - Reduce costs for high-volume tasks - Run async jobs without blocking - Process large datasets with AI - Generate multiple documents at once - Create scalable content pipelines - Process requests that don't need real-time responses ## Available Scripts ### scripts/create_batch.py **Purpose**: Create a batch job from a JSONL file **When to use**: - Starting any batch processing task - Uploading multiple requests for processing - Creating async jobs for large workloads **Key parameters**: | Parameter | Description | Example | |-----------|-------------|---------| | `input_file` | JSONL file path (required) | `requests.jsonl` | | `--model`, `-m` | Model to use | `gemini-3-flash-preview` | | `--name`, `-n` | Display name for job | `"my-batch-job"` | **Output**: Job name/ID to track with check_status.py ### scripts/check_status.py **Purpose**: Monitor batch job progress and
- When to Use This Skill
- Available Scripts
- scripts/createbatch.py
- scripts/checkstatus.py
- scripts/getresults.py
- Workflows
- Workflow 1: Basic Batch Processing
- Workflow 2: Bulk Content Generation
- Workflow 3: Dataset Processing
- Workflow 4: Email Campaign Generation
- Workflow 5: Async Job Monitoring
- Workflow 6: Cost-Optimized Bulk Processing
- Workflow 7: Multi-Stage Pipeline
- Parameters Reference
echo '{"key": "req1", "request": {"contents": [{"parts": [{"text": "Explain photosynthesis"}]}]}}' > requests.jsonl
echo '{"key": "req2", "request": {"contents": [{"parts": [{"text": "What is gravity?"}]}}]}' >> requests.jsonl
python scripts/create_batch.py requests.jsonl --name "science-questions"
python scripts/check_status.py <job-name> --wait
python scripts/get_results.py <job-name> --output results.jsonl
python3 << 'EOF'
python scripts/create_batch.py content-requests.jsonl --name "blog-posts" --model gemini-3-flash-preview
python scripts/get_results.py <job-name> --output blog-posts.jsonl
python scripts/create_batch.py product-descriptions.jsonl
python scripts/create_batch.py emails.jsonl --name "email-campaign"What does the gemini-batch skill do?
Process large volumes of requests using Gemini Batch API via scripts/. Use for batch processing, bulk text generation, processing JSONL files, async job execution, and cost-efficient high-volume AI tasks. Triggers on "batch processing", "bulk requests", "JSONL", "async job", "batch job".
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill gemini-batch-akrindev-google-studio-skills --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.