The PraisonAI CLI automatically tracks and displays tool calls made by agents, providing visibility into what actions the AI is taking.
Overview
When you run a prompt, the CLI:
- Loads 5 built-in tools by default
- Tracks all tool calls made during execution
- Displays a summary of tools used after completion
Every CLI prompt has access to these 5 built-in tools:
| Tool | Description | Example Use |
|---|
read_file | Read file contents | ”Read README.md” |
write_file | Write to files | ”Create a hello.py file” |
list_files | List directory contents | ”List files here” |
execute_command | Run shell commands | ”Run ls -la” |
internet_search | Search the web | ”Search for Python tutorials” |
Usage Examples
# Agent automatically uses list_files
praisonai "List all files in current directory"
Tools used: list_files
- file1.py
- file2.py
- README.md
...
# Agent uses multiple tools to complete the task
praisonai "Read the README.md file and summarize it"
Tools used: list_files, read_file
This project is about...
Verbose Mode
For detailed tool call information, use verbose mode:
praisonai "List files" -v
╭─ Agent Info ─────────────────────────────────────────────────────────────────╮
│ │
│ 👤 Agent: DirectAgent │
│ Role: Assistant │
│ Tools: read_file, write_file, list_files, execute_command, internet_search │
│ │
╰──────────────────────────────────────────────────────────────────────────────╯
╭───────── Tool Call ──────────╮
│ Calling function: list_files │
╰──────────────────────────────╯
Arguments: {'directory': '.'}
╭───────────────────────────────── Tool Call ──────────────────────────────────╮
│ Function list_files returned: [{"name": "file1.py", ...}] │
╰──────────────────────────────────────────────────────────────────────────────╯
Response generated in 2.5s
╭──────────────────────────────────── Task ────────────────────────────────────╮
│ List files │
╰──────────────────────────────────────────────────────────────────────────────╯
╭────────────────────────────────── Response ──────────────────────────────────╮
│ - file1.py │
│ - file2.py │
│ - README.md │
╰──────────────────────────────────────────────────────────────────────────────╯
--tools flag:
# Load tools from a Python file
praisonai "Analyze data" --tools my_tools.py
def analyze_csv(filepath: str) -> dict:
"""Analyze a CSV file and return statistics."""
import pandas as pd
df = pd.read_csv(filepath)
return {
"rows": len(df),
"columns": list(df.columns),
"summary": df.describe().to_dict()
}
Callback System
The tool tracking uses a callback system that can be extended programmatically:
from praisonaiagents import register_display_callback
def my_tool_callback(message):
"""Custom callback for tool calls."""
print(f"🔧 Tool activity: {message}")
# Register the callback
register_display_callback('tool_call', my_tool_callback)
Comparison: Default vs Verbose
| Feature | Default Mode | Verbose Mode (-v) |
|---|
| Tool summary | ✅ “Tools used: X, Y” | ✅ Full panels |
| Arguments | ❌ Hidden | ✅ Shown |
| Return values | ❌ Hidden | ✅ Shown (truncated) |
| Agent info | ❌ Hidden | ✅ Full panel |
| Response time | ❌ Hidden | ✅ Shown |
Best Practices
Use default mode for clean output in scripts and pipelines. Use verbose mode (-v) when debugging or learning what the agent is doing.
Tool calls are tracked via a callback system that has zero performance overhead when no callback is registered.
Interactive Mode
Full interactive TUI with tool support
Tools Management
Discover and manage available tools
Cost Tracking
Track token usage and costs
Verbose Output
Detailed output options
