Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Productivity
Ai Automation Workflows
Build automated AI workflows combining multiple models and services. Patterns: batch processing, scheduled tasks, event-driven pipelines, agent loops. Tools:...
skill openclawclawhub Free
Build automated AI workflows combining multiple models and services. Patterns: batch processing, scheduled tasks, event-driven pipelines, agent loops. Tools:...
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
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Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 0.1.5
Provenance
- Publisher
- okaris
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
AI Automation Workflows
Build automated AI workflows via inference.sh CLI.
Quick Start
curl -fsSL https://cli.inference.sh | sh && infsh login # Simple automation: Generate daily image infsh app run falai/flux-dev --input '{ "prompt": "Inspirational quote background, minimalist design, date: '"$(date +%Y-%m-%d)"'" }' Install note: The install script only detects your OS/architecture, downloads the matching binary from dist.inference.sh, and verifies its SHA-256 checksum. No elevated permissions or background processes. Manual install & verification available.
Pattern 1: Batch Processing
Process multiple items with the same workflow. #!/bin/bash # batch_images.sh - Generate images for multiple prompts PROMPTS=( "Mountain landscape at sunrise" "Ocean waves at sunset" "Forest path in autumn" "Desert dunes at night" ) for prompt in "${PROMPTS[@]}"; do echo "Generating: $prompt" infsh app run falai/flux-dev --input "{ \"prompt\": \"$prompt, professional photography, 4K\" }" > "output_${prompt// /_}.json" sleep 2 # Rate limiting done
Pattern 2: Sequential Pipeline
Chain multiple AI operations. #!/bin/bash # content_pipeline.sh - Full content creation pipeline TOPIC="AI in healthcare" # Step 1: Research echo "Researching..." RESEARCH=$(infsh app run tavily/search-assistant --input "{ \"query\": \"$TOPIC latest developments\" }") # Step 2: Write article echo "Writing article..." ARTICLE=$(infsh app run openrouter/claude-sonnet-45 --input "{ \"prompt\": \"Write a 500-word blog post about $TOPIC based on: $RESEARCH\" }") # Step 3: Generate image echo "Generating image..." IMAGE=$(infsh app run falai/flux-dev --input "{ \"prompt\": \"Blog header image for article about $TOPIC, modern, professional\" }") # Step 4: Generate social post echo "Creating social post..." SOCIAL=$(infsh app run openrouter/claude-haiku-45 --input "{ \"prompt\": \"Write a Twitter thread (5 tweets) summarizing: $ARTICLE\" }") echo "Pipeline complete!"
Pattern 3: Parallel Processing
Run multiple operations simultaneously. #!/bin/bash # parallel_generation.sh - Generate multiple assets in parallel # Start all jobs in background infsh app run falai/flux-dev --input '{"prompt": "Hero image..."}' > hero.json & PID1=$! infsh app run falai/flux-dev --input '{"prompt": "Feature image 1..."}' > feature1.json & PID2=$! infsh app run falai/flux-dev --input '{"prompt": "Feature image 2..."}' > feature2.json & PID3=$! # Wait for all to complete wait $PID1 $PID2 $PID3 echo "All images generated!"
Pattern 4: Conditional Workflow
Branch based on results. #!/bin/bash # conditional_workflow.sh - Process based on content analysis INPUT_TEXT="$1" # Analyze content ANALYSIS=$(infsh app run openrouter/claude-haiku-45 --input "{ \"prompt\": \"Classify this text as: positive, negative, or neutral. Return only the classification.\n\n$INPUT_TEXT\" }") # Branch based on result case "$ANALYSIS" in *positive*) echo "Generating celebration image..." infsh app run falai/flux-dev --input '{"prompt": "Celebration, success, happy"}' ;; *negative*) echo "Generating supportive message..." infsh app run openrouter/claude-sonnet-45 --input "{ \"prompt\": \"Write a supportive, encouraging response to: $INPUT_TEXT\" }" ;; *) echo "Generating neutral acknowledgment..." ;; esac
Pattern 5: Retry with Fallback
Handle failures gracefully. #!/bin/bash # retry_workflow.sh - Retry failed operations generate_with_retry() { local prompt="$1" local max_attempts=3 local attempt=1 while [ $attempt -le $max_attempts ]; do echo "Attempt $attempt..." result=$(infsh app run falai/flux-dev --input "{\"prompt\": \"$prompt\"}" 2>&1) if [ $? -eq 0 ]; then echo "$result" return 0 fi echo "Failed, retrying..." ((attempt++)) sleep $((attempt * 2)) # Exponential backoff done # Fallback to different model echo "Falling back to alternative model..." infsh app run google/imagen-3 --input "{\"prompt\": \"$prompt\"}" } generate_with_retry "A beautiful sunset over mountains"
Cron Job Setup
# Edit crontab crontab -e # Daily content generation at 9 AM 0 9 * * * /path/to/daily_content.sh >> /var/log/ai-automation.log 2>&1 # Weekly report every Monday at 8 AM 0 8 * * 1 /path/to/weekly_report.sh >> /var/log/ai-automation.log 2>&1 # Every 6 hours: social media content 0 */6 * * * /path/to/social_content.sh >> /var/log/ai-automation.log 2>&1
Daily Content Script
#!/bin/bash # daily_content.sh - Run daily at 9 AM DATE=$(date +%Y-%m-%d) OUTPUT_DIR="/output/$DATE" mkdir -p "$OUTPUT_DIR" # Generate daily quote image infsh app run falai/flux-dev --input '{ "prompt": "Motivational quote background, minimalist, morning vibes" }' > "$OUTPUT_DIR/quote_image.json" # Generate daily tip infsh app run openrouter/claude-haiku-45 --input '{ "prompt": "Give me one actionable productivity tip for today. Be concise." }' > "$OUTPUT_DIR/daily_tip.json" # Post to social (optional) # infsh app run twitter/post-tweet --input "{...}" echo "Daily content generated: $DATE"
Logging Wrapper
#!/bin/bash # logged_workflow.sh - With comprehensive logging LOG_FILE="/var/log/ai-workflow-$(date +%Y%m%d).log" log() { echo "[$(date '+%Y-%m-%d %H:%M:%S')] $1" | tee -a "$LOG_FILE" } log "Starting workflow" # Track execution time START_TIME=$(date +%s) # Run workflow log "Generating image..." RESULT=$(infsh app run falai/flux-dev --input '{"prompt": "test"}' 2>&1) STATUS=$? if [ $STATUS -eq 0 ]; then log "Success: Image generated" else log "Error: $RESULT" fi END_TIME=$(date +%s) DURATION=$((END_TIME - START_TIME)) log "Completed in ${DURATION}s"
Error Alerting
#!/bin/bash # monitored_workflow.sh - With error alerts run_with_alert() { local result result=$("$@" 2>&1) local status=$? if [ $status -ne 0 ]; then # Send alert (webhook, email, etc.) curl -X POST "https://your-webhook.com/alert" \ -H "Content-Type: application/json" \ -d "{\"error\": \"$result\", \"command\": \"$*\"}" fi echo "$result" return $status } run_with_alert infsh app run falai/flux-dev --input '{"prompt": "test"}'
Python SDK Automation
#!/usr/bin/env python3 # automation.py - Python-based workflow import subprocess import json from datetime import datetime from pathlib import Path def run_infsh(app_id: str, input_data: dict) -> dict: """Run inference.sh app and return result.""" result = subprocess.run( ["infsh", "app", "run", app_id, "--input", json.dumps(input_data)], capture_output=True, text=True ) return json.loads(result.stdout) if result.returncode == 0 else None def daily_content_pipeline(): """Generate daily content.""" date_str = datetime.now().strftime("%Y-%m-%d") output_dir = Path(f"output/{date_str}") output_dir.mkdir(parents=True, exist_ok=True) # Generate image image = run_infsh("falai/flux-dev", { "prompt": f"Daily inspiration for {date_str}, beautiful, uplifting" }) (output_dir / "image.json").write_text(json.dumps(image)) # Generate caption caption = run_infsh("openrouter/claude-haiku-45", { "prompt": "Write an inspiring caption for a daily motivation post. 2-3 sentences." }) (output_dir / "caption.json").write_text(json.dumps(caption)) print(f"Generated content for {date_str}") if __name__ == "__main__": daily_content_pipeline()
Content Calendar Automation
#!/bin/bash # content_calendar.sh - Generate week of content TOPICS=("productivity" "wellness" "technology" "creativity" "leadership") DAYS=("Monday" "Tuesday" "Wednesday" "Thursday" "Friday") for i in "${!DAYS[@]}"; do DAY=${DAYS[$i]} TOPIC=${TOPICS[$i]} echo "Generating $DAY content about $TOPIC..." # Image infsh app run falai/flux-dev --input "{ \"prompt\": \"$TOPIC theme, $DAY motivation, social media style\" }" > "content/${DAY}_image.json" # Caption infsh app run openrouter/claude-haiku-45 --input "{ \"prompt\": \"Write a $DAY motivation post about $TOPIC. Include hashtags.\" }" > "content/${DAY}_caption.json" done
Data Processing Pipeline
#!/bin/bash # data_processing.sh - Process and analyze data files INPUT_DIR="./data/raw" OUTPUT_DIR="./data/processed" for file in "$INPUT_DIR"/*.txt; do filename=$(basename "$file" .txt) # Analyze content infsh app run openrouter/claude-haiku-45 --input "{ \"prompt\": \"Analyze this data and provide key insights in JSON format: $(cat $file)\" }" > "$OUTPUT_DIR/${filename}_analysis.json" done
Best Practices
Rate limiting - Add delays between API calls Error handling - Always check return codes Logging - Track all operations Idempotency - Design for safe re-runs Monitoring - Alert on failures Backups - Save intermediate results Timeouts - Set reasonable limits
Related Skills
# Content pipelines npx skills add inference-sh/skills@ai-content-pipeline # RAG pipelines npx skills add inference-sh/skills@ai-rag-pipeline # Social media automation npx skills add inference-sh/skills@ai-social-media-content # Full platform skill npx skills add inference-sh/skills@inference-sh Browse all apps: infsh app list
Category context
Workflow acceleration for inboxes, docs, calendars, planning, and execution loops.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs
- SKILL.md