# Send Ai Automation Workflows to your agent
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
## Fast path
- 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.
## Suggested prompts
### New install

```text
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

```text
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
```
## Machine-readable fields
```json
{
  "schemaVersion": "1.0",
  "item": {
    "slug": "ai-automation-workflows",
    "name": "Ai Automation Workflows",
    "source": "tencent",
    "type": "skill",
    "category": "效率提升",
    "sourceUrl": "https://clawhub.ai/okaris/ai-automation-workflows",
    "canonicalUrl": "https://clawhub.ai/okaris/ai-automation-workflows",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadUrl": "/downloads/ai-automation-workflows",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=ai-automation-workflows",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "packageFormat": "ZIP package",
    "primaryDoc": "SKILL.md",
    "includedAssets": [
      "SKILL.md"
    ],
    "downloadMode": "redirect",
    "sourceHealth": {
      "source": "tencent",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-04-23T16:43:11.935Z",
      "expiresAt": "2026-04-30T16:43:11.935Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=4claw-imageboard",
        "contentDisposition": "attachment; filename=\"4claw-imageboard-1.0.1.zip\"",
        "redirectLocation": null,
        "bodySnippet": null
      },
      "scope": "source",
      "summary": "Source download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/ai-automation-workflows"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    }
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/ai-automation-workflows",
    "downloadUrl": "https://openagent3.xyz/downloads/ai-automation-workflows",
    "agentUrl": "https://openagent3.xyz/skills/ai-automation-workflows/agent",
    "manifestUrl": "https://openagent3.xyz/skills/ai-automation-workflows/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/ai-automation-workflows/agent.md"
  }
}
```
## 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
## Trust
- Source: tencent
- Verification: Indexed source record
- Publisher: okaris
- Version: 0.1.5
## Source health
- Status: healthy
- Source download looks usable.
- Yavira can redirect you to the upstream package for this source.
- Health scope: source
- Reason: direct_download_ok
- Checked at: 2026-04-23T16:43:11.935Z
- Expires at: 2026-04-30T16:43:11.935Z
- Recommended action: Download for OpenClaw
## Links
- [Detail page](https://openagent3.xyz/skills/ai-automation-workflows)
- [Send to Agent page](https://openagent3.xyz/skills/ai-automation-workflows/agent)
- [JSON manifest](https://openagent3.xyz/skills/ai-automation-workflows/agent.json)
- [Markdown brief](https://openagent3.xyz/skills/ai-automation-workflows/agent.md)
- [Download page](https://openagent3.xyz/downloads/ai-automation-workflows)