Agent Toolsets¶
What are Toolsets?¶
Toolsets in LLMling define groups of related tools that agents can access. Rather than configuring individual tool permissions, you enable entire categories of functionality through toolset configurations.
Think of toolsets as "skill packages" that give agents specific capabilities - from file operations to process management to agent coordination.
Available Toolsets¶
Agent Management (agent_management)¶
Enables agents to discover, coordinate with, and manage other agents:
Provides tools:
- list_available_agents - Discover other agents in the pool
- list_available_teams - Discover available teams
- delegate_to - Assign tasks to other agents
- ask_agent - Ask other agents directly
- add_agent - Add new agents to the pool
- add_team - Create new teams
- connect_nodes - Connect agents/teams in workflows
- create_worker_agent - Create worker agents as tools
- spawn_delegate - Create temporary delegate agents
File Access (file_access)¶
Basic file system operations:
Provides tools:
- read_file - Read local and remote files
- list_directory - List directory contents
Resource Access (resource_access)¶
Access to LLMling resources and configurations:
Provides tools:
- load_resource - Load resource content
- get_resources - Discover available resources
Code Execution (code_execution)¶
Execute Python code and system commands:
Provides tools:
- execute_python - Execute Python code (WARNING: No sandbox)
- execute_command - Execute CLI commands
Process Management (process_management)¶
Start and manage background processes:
Provides tools:
- start_process - Start background processes
- get_process_output - Check process output
- wait_for_process - Wait for process completion
- kill_process - Terminate processes
- release_process - Clean up process resources
- list_processes - Show active processes
Tool Management (tool_management)¶
Register and manage tools dynamically:
Provides tools:
- register_tool - Register importable functions as tools
- register_code_tool - Create tools from code
- install_package - Install Python packages
User Interaction (user_interaction)¶
Direct interaction with users:
Provides tools:
- ask_user - Ask users clarifying questions
History (history)¶
Access conversation history and statistics:
Provides tools:
- search_history - Search conversation history
- show_statistics - Display usage statistics
Integrations (integrations)¶
External service integrations:
Provides tools:
- add_local_mcp_server - Add local MCP servers
- add_remote_mcp_server - Add remote MCP servers
- load_skill - Load Claude Code Skills
Common Patterns¶
Basic Assistant¶
agents:
assistant:
model: openai:gpt-4
toolsets:
- type: resource_access
- type: file_access
- type: user_interaction
Team Coordinator¶
agents:
coordinator:
model: openai:gpt-4
toolsets:
- type: agent_management
- type: history
system_prompts:
- You coordinate tasks across multiple agents
Developer Agent¶
agents:
developer:
model: anthropic:claude-3-5-sonnet-20241022
toolsets:
- type: file_access
- type: code_execution
- type: process_management
- type: tool_management
system_prompts:
- You are a software developer with full system access
Restricted Agent¶
agents:
restricted:
model: openai:gpt-4-mini
toolsets: [] # No toolsets = only predefined tools
tools:
- calculator
- web_search
Security Considerations¶
Toolsets provide different levels of system access:
Low Risk:
- file_access - Read-only file operations
- resource_access - Access to configured resources
- user_interaction - User prompts only
Medium Risk:
- agent_management - Can create and coordinate agents
- history - Access to conversation data
- integrations - External service access
High Risk:
- code_execution - Can execute arbitrary code
- process_management - System process control
- tool_management - Can modify available tools
Always use the principle of least privilege - only enable toolsets that agents actually need.
Custom Toolsets¶
You can also create custom toolsets by implementing your own provider:
See the Custom Tools guide for implementation details.