agent operations skill risk: medium
CLI Agent Manager via Tmux Sessions
The prompt provides instructions for using a tmux-based agent-manager-skill to start, stop, monitor, assign tasks to, and schedule multiple local CLI agents, including prerequisite…
- External action: high
SKILL 1 file
SKILL.md
--- name: agent-manager-skill description: "Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling." --- # Agent Manager Skill ## When to Use Use this skill when you need to: - run multiple local CLI agents in parallel (separate tmux sessions) - start/stop agents and tail their logs - assign tasks to agents and monitor output - schedule recurring agent work (cron) ## Prerequisites Install `agent-manager-skill` in your workspace: ```bash git clone https://github.com/fractalmind-ai/agent-manager-skill.git ``` ## Common commands ```bash python3 agent-manager/scripts/main.py doctor python3 agent-manager/scripts/main.py list python3 agent-manager/scripts/main.py start EMP_0001 python3 agent-manager/scripts/main.py monitor EMP_0001 --follow python3 agent-manager/scripts/main.py assign EMP_0002 <<'EOF' Follow teams/fractalmind-ai-maintenance.md Workflow EOF ``` ## Notes - Requires `tmux` and `python3`. - Agents are configured under an `agents/` directory (see the repo for examples). ## Limitations - Use this skill only when the task clearly matches the scope described above. - Do not treat the output as a substitute for environment-specific validation, testing, or expert review. - Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
REQUIRED CONTEXT
- tmux
- python3
- agents/ directory
ROLES & RULES
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
EXPECTED OUTPUT
- Format
- markdown
EXAMPLES
Includes bash installation command and five example CLI invocations with agent IDs and heredoc input.
CAVEATS
- Missing context
- Agent configuration schema or directory structure
- Error handling or permission requirements for tmux sessions
- Ambiguities
- 'see the repo for examples' leaves agent configuration details unspecified
- Reference to external workflow file 'teams/fractalmind-ai-maintenance.md' is unexplained
QUALITY
- OVERALL
- 0.55
- CLARITY
- 0.78
- SPECIFICITY
- 0.65
- REUSABILITY
- 0.35
- COMPLETENESS
- 0.60
IMPROVEMENT SUGGESTIONS
- Replace the hardcoded GitHub clone URL and script paths with placeholders
- Add a required 'Success Criteria' section to the When to Use guidance
USAGE
Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.
MORE FOR AGENT
- Local Documentation Online Sync Automatoragentoperations
- HashiCorp Packer Golden Image Expertagentoperations
- ML Experiment GPU Deployment Workflowagentoperations
- Codex Training Metrics Monitoragentoperations
- Context Optimization Techniques Guideagentoperations
- Issue Triage State Machineagentoperations
- ML Experiment Results Monitoragentoperations
- DOCX Document Creation Editing Guideagentoperations
- Repo Agent Skills Configuration Setupagentoperations
- Git Worktree Isolated Workspace Setupagentoperations
- Agent Context Compression Strategiesagentoperations
- Parallel Agent Dispatcher for Independent Tasksagentoperations
- Scientific Computing Resource Detectoragentoperations
- PPTX File Handling Skill Guideagentoperations
- Interactive QA GitHub Issue Fileragentoperations
- Sprint Retrospective Facilitatoragentoperations
- Agent Skill Writing Guideagentoperations
- Brilliant Directories Rube MCP Automation Guideagentoperations
- Istio Linkerd Service Mesh Expertagentoperations
- Machine Learning Experiment Monitoragentoperations
- Benchling Python SDK Integrationagentoperations
- Blackbaud Automation via Rube MCPagentoperations
- DigitalOcean Automation via Rube MCPagentoperations
- Service Mesh Architecture Expertagentoperations
- WandB Training Metrics Health Checkeragentoperations