run-other-cli-agents
- Repo stars 0
- Author updated Live
- Author repo nano-core
- Domain
- Data
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @0-CYBERDYNE-SYSTEMS-0 · no license declared
- Token usage
- Lean
- Setup complexity
- Manual integration
- External API key
- Not required
- Operating systems
- macOS · Docker
- Runtime requirements
- Docker
- Permissions
-
- Read-only
- Shell exec
- Env read
- Write / modify
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: run-other-cli-agents
description: Execute and orchestrate external CLI-based agents to delegate subtasks, obtain specialized outpu…
category: data
runtime: Docker
---
# run-other-cli-agents output preview
## PART A: Task fit
- Use case: 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..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “When to use this skill / When not to use this skill / Core Capabilities” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “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.”.
- **02** When the source has headings, the agent prioritizes “When to use this skill / When not to use this skill / Core Capabilities” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, run shell commands, read environment variables, write/modify files; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, run shell commands, read environment variables, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source mentions slash commands such as `/users`, `/tmp`, `/data`, `/path`; use them first when your agent supports command triggers.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, run shell commands, read environment variables, write/modify files.
Start with a small task and check whether the result follows “When to use this skill / When not to use this skill / Core Capabilities”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: run-other-cli-agents
description: Execute and orchestrate external CLI-based agents to delegate subtasks, obtain specialized outpu…
category: data
source: 0-CYBERDYNE-SYSTEMS-0/nano-core
---
# run-other-cli-agents
## When to use
- Execute and orchestrate external CLI-based agents to delegate subtasks, obtain specialized outputs, or compose multi-a…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “When to use this skill / When not to use this skill / Core Capabilities” and keep inference separate from source facts.
- read files, run shell commands, read environment variables, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "run-other-cli-agents" {
input -> user goal + target files + boundaries + acceptance criteria
context -> When to use this skill / When not to use this skill / Core Capabilities
rules -> SKILL.md triggers / order / output contract
runtime -> Docker | read files, run shell commands, read environment variables, write/modify files | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} 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 secondsMAX_RETRIES- Default retry countRETRY_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
- Always use timeouts - Prevent runaway agents with
--timeout - Validate output - Use
--formatto ensure expected output structure - Handle errors - Use
--retryfor network-dependent agents - Isolate untrusted code - Always use
--sandboxfor third-party agents - Log everything - Review logs in
$AGENT_LOG_DIRfor debugging - Clean up - Remove old logs periodically to save disk space
- Test in isolation - Run new agents standalone before chaining
- Use quiet mode in scripts - Add
--quietto reduce log noise - Monitor resources - Check CPU/memory usage for long-running agents
- 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
--asyncfor long-running agents to avoid blocking - Run independent agents in parallel with
&andwait - Set appropriate timeouts to free resources quickly
- Use
--quietin scripts to reduce I/O overhead - Clean up old logs in
$AGENT_LOG_DIRregularly - Consider agent pooling for high-frequency invocations
- Use
--format jsonwhen 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
Decide Fit First
Design Intent
How To Use It
Boundaries And Review