run-other-cli-agents

name

run-other-cli-agents

description

Execute and orchestrate external CLI-based agents to delegate subtasks, obtain specialized outputs, or compose multi-agent workflows. Use this skill when: (1) A task requires capabilities from specialized external agents (math, weather, data processing, API clients, etc.), (2) You need to parallelize work across multiple agent instances, (3) Building multi-stage pipelines where different agents handle different processing stages, (4) Delegating to domain-specific agents for better results, (5) Running untrusted third-party agents safely with sandboxing, or (6) Orchestrating async/background agent execution for long-running tasks. Requires bash tool access and target CLI agents available in PATH.

Run Other CLI Agents

When to use this skill

• Use when the user request matches this skill's domain and capabilities.
• Use when this workflow or toolchain is explicitly requested.

When not to use this skill

• Do not use when another skill is a better direct match for the task.
• Do not use when the request is outside this skill's scope.

Execute external CLI agents safely with comprehensive error handling, async execution, output format detection, and security controls.

Core Capabilities

• Safe Execution: Built-in error handling, retries, and timeout management
• Async Mode: Run agents in background for long-running tasks
• Format Detection: Auto-detect and validate JSON, XML, or text output
• Sandboxing: Execute untrusted agents with filesystem and network isolation
• Agent Chaining: Pipe output from one agent to another
• Parallel Execution: Run multiple agents simultaneously
• Resource Management: Control CPU, memory, and timeout limits
• Audit Logging: Track all agent invocations and results

Quick Start

Basic Invocation

./scripts/run_agent.sh math-agent "Calculate sqrt(144)"

With Advanced Features

# Async execution with retry and JSON output
./scripts/run_agent.sh --async --retry 3 --format json api-agent "GET /users"

# Sandboxed untrusted agent
./scripts/run_agent.sh --sandbox --timeout 30 third-party-agent "Process data"

Using the Helper Script

The scripts/run_agent.sh script provides robust agent execution with multiple options:

Command Syntax

./scripts/run_agent.sh [OPTIONS] <agent_command> "task description" [agent_args...]

Common Options

• --async - Run agent in background, return immediately with run ID
• --timeout N - Set timeout in seconds (default: 300)
• --retry N - Retry N times on failure (default: 0)
• --format FMT - Expected output format: json|text|auto (default: auto)
• --sandbox - Run in restricted sandbox (requires firejail)
• --quiet - Suppress informational output
• --help - Show full help message

Environment Variables

• AGENT_LOG_DIR - Log directory (default: /tmp/agent_logs)
• AGENT_TIMEOUT - Default timeout in seconds
• MAX_RETRIES - Default retry count
• RETRY_DELAY - Delay between retries in seconds

Common Patterns

Agent Chaining

Connect multiple agents in a pipeline:

# Extract → Transform → Load
raw=$(./scripts/run_agent.sh extractor "Extract from source")
transformed=$(./scripts/run_agent.sh transformer "$raw")
./scripts/run_agent.sh loader "$transformed"

Parallel Execution

Run multiple agents simultaneously:

./scripts/run_agent.sh agent1 "Task 1" &
./scripts/run_agent.sh agent2 "Task 2" &
./scripts/run_agent.sh agent3 "Task 3" &
wait

Async with Status Checking

Launch long-running agents in background:

# Start async
RUN_ID=$(./scripts/run_agent.sh --async data-processor "Process large_dataset.csv")

# Check status
PID=$(cat /tmp/agent_logs/${RUN_ID}.pid)
kill -0 $PID 2>/dev/null && echo "Running" || echo "Done"

# Get results
cat /tmp/agent_logs/${RUN_ID}.out

Error Recovery

Handle failures with retries:

./scripts/run_agent.sh --retry 3 --timeout 60 flaky-agent "Task"

Format Validation

Ensure output is valid JSON:

./scripts/run_agent.sh --format json api-agent "GET /data" | jq '.results'

Security Considerations

When running untrusted or third-party agents, always use security controls. See references/security.md for comprehensive security guidance including:

• Sandboxing with firejail, Docker, or platform-specific tools
• Input validation and sanitization
• Output sanitization for sensitive data
• Resource limits (CPU, memory, disk, network)
• File system access control
• Secrets management
• Audit logging

Quick Security Example

# Run untrusted agent with multiple protections
./scripts/run_agent.sh \
    --sandbox \
    --timeout 30 \
    --format json \
    --quiet \
    untrusted-agent "task"

Advanced Usage

Multi-Stage Pipeline with Checkpoints

Build resilient pipelines that can resume after failures:

# Stage 1
if [ ! -f .stage1_done ]; then
    ./scripts/run_agent.sh --retry 3 stage1-agent "Extract" && touch .stage1_done
fi

# Stage 2
if [ ! -f .stage2_done ]; then
    ./scripts/run_agent.sh --retry 3 stage2-agent "Transform" && touch .stage2_done
fi

# Stage 3
./scripts/run_agent.sh --retry 3 stage3-agent "Load"

Load Balancing

Distribute tasks across agent pool:

AGENTS=("agent-1" "agent-2" "agent-3")
TASKS=("task1" "task2" "task3" "task4" "task5")

i=0
for task in "${TASKS[@]}"; do
    agent="${AGENTS[$((i % ${#AGENTS[@]}))]}"
    ./scripts/run_agent.sh --async "$agent" "$task"
    i=$((i + 1))
done
wait

Conditional Agent Selection

Route to specialized agents based on input:

case "$REQUEST_TYPE" in
    "weather")
        ./scripts/run_agent.sh weather-agent "$REQUEST_DATA"
        ;;
    "stocks")
        ./scripts/run_agent.sh --format json stock-agent "$REQUEST_DATA"
        ;;
    "news")
        ./scripts/run_agent.sh news-agent "$REQUEST_DATA"
        ;;
esac

Reference Documentation

For detailed examples and security guidance, see:

• references/examples.md - Comprehensive usage examples including:

  • Basic and advanced invocations
  • Async and background execution patterns
  • Error handling and retry strategies
  • Output format detection and validation
  • Agent chaining and pipeline patterns
  • Parallel execution with xargs and background jobs
  • Real-world scenarios (web scraping, ML workflows, ETL pipelines)
  • Monitoring and alerting patterns

• references/security.md - Security best practices including:

  • Threat model and risk assessment
  • Sandboxing with firejail, Docker, macOS sandbox
  • Input validation and sanitization
  • Output sanitization for sensitive data
  • Resource limits (CPU, memory, disk, network)
  • Network isolation techniques
  • File system access control
  • Secrets management
  • Audit logging
  • Complete security checklist

Troubleshooting

Agent Not Found

# Check if agent is in PATH
command -v agent-name

# List available agents
compgen -c | grep -E 'agent|cli'

Timeout Issues

# Increase timeout
./scripts/run_agent.sh --timeout 600 slow-agent "task"

# Or set environment variable
AGENT_TIMEOUT=600 ./scripts/run_agent.sh slow-agent "task"

Output Format Problems

# Let script detect format
./scripts/run_agent.sh --format auto agent "task"

# Or specify expected format
./scripts/run_agent.sh --format json agent "task"

Permission Errors

# Ensure script is executable
chmod +x scripts/run_agent.sh

# Check log directory permissions
mkdir -p /tmp/agent_logs
chmod 755 /tmp/agent_logs

Best Practices

1. Always use timeouts - Prevent runaway agents with --timeout
2. Validate output - Use --format to ensure expected output structure
3. Handle errors - Use --retry for network-dependent agents
4. Isolate untrusted code - Always use --sandbox for third-party agents
5. Log everything - Review logs in $AGENT_LOG_DIR for debugging
6. Clean up - Remove old logs periodically to save disk space
7. Test in isolation - Run new agents standalone before chaining
8. Use quiet mode in scripts - Add --quiet to reduce log noise
9. Monitor resources - Check CPU/memory usage for long-running agents
10. Version control agents - Track which agent versions are deployed

Integration Examples

With CI/CD Pipeline

# .github/workflows/agent-tests.yml
- name: Test agents
  run: |
    ./scripts/run_agent.sh --timeout 30 test-agent "Run tests"

With Cron Jobs

# Hourly monitoring
0 * * * * /path/to/run_agent.sh monitor-agent "Check system health"

With Systemd Services

[Unit]
Description=Background Agent Processor

[Service]
ExecStart=/path/to/run_agent.sh --async processor-agent "Process queue"
Restart=always

[Install]
WantedBy=multi-user.target

Performance Tips

• Use --async for long-running agents to avoid blocking
• Run independent agents in parallel with & and wait
• Set appropriate timeouts to free resources quickly
• Use --quiet in scripts to reduce I/O overhead
• Clean up old logs in $AGENT_LOG_DIR regularly
• Consider agent pooling for high-frequency invocations
• Use --format json when output needs parsing (faster than regex)

Direct Invocation (Alternative)

If you don't need the wrapper's features, invoke agents directly:

agent-name "task description" [args...]

However, the wrapper script provides significant benefits:

• Automatic error handling and logging
• Timeout and retry capabilities
• Format detection and validation
• Security controls
• Consistent interface across all agents