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ai-monitor

Proactive system monitoring daemon with anomaly detection and suggestions

Version: 9.0.1 | Size: 4.0MB | Author: Warith Al Maawali

License: Proprietary | Website: https://www.digi77.com

File Information

Property Value
Binary Name ai-monitor
Version 9.0.1
Build Date REDACTED-BUILD-TIME
Rust Version 1.82.0
File Size 4.0MB
Author Warith Al Maawali
License Proprietary
Category Kodachi Binary
Description Proactive system monitoring daemon with anomaly detection and suggestions
Git Commit unknown
Metadata Generated 2026-06-08T16:22:07Z
Binary Timestamp Unknown
JSON Data View Raw JSON

SHA256 Checksum

d9c3be8c19b62aedf55cc7018194a7825f0ac78569b745b33bd3fc0b13aed256

Features

# Feature
1 Advanced functionality for Kodachi OS

Security Features

Feature Description
Input Validation Argument parsing via clap; per-command validation is the consumer's responsibility
Rate Limiting Not provided by cli-core
Authentication Not provided by cli-core (see online-auth)
Encryption Not provided by cli-core

System Requirements

Requirement Value
OS Linux (Debian-based)
Privileges root/sudo for system operations
Dependencies OpenSSL, libcurl

Global Options

Flag Description
-h, --help Print help information
-v, --version Print version information
-n, --info Display detailed information
-e, --examples Show usage examples
--json Output in JSON format
-o, --output-format <FORMAT> Force output format (text
--json-pretty Pretty-print JSON output with indentation
--json-human Enhanced JSON output with improved formatting (like jq)
--fields <FIELD_LIST> Select specific fields to include in output (comma-separated)
--limit <NUMBER> Limit number of results returned
--offset <NUMBER> Skip first N results (for pagination)
-d, --work-dir <PATH> Working directory (defaults to auto-detected base directory)
--port <PORT> Set custom port number (1024-65535)
--log-level <LEVEL> Set log level (error
--verbose Enable verbose output
--quiet Suppress non-essential output
--no-color Disable colored output
--config <FILE> Use custom configuration file
--timeout <SECS> Set operation timeout in seconds (optional; no default applied)
--retry <COUNT> Retry attempts (optional; no default applied)

Commands

Commands

start

Start the system monitoring daemon

Usage: 

ai-monitor start [OPTIONS]

Options: - --interval: Check interval in seconds - --threshold: Security score threshold - --daemon: Run as background daemon

Examples: 

ai-monitor start

ai-monitor start --interval 60

ai-monitor start --threshold 80

ai-monitor start --daemon

status

Show current monitor status and statistics

Usage: 

ai-monitor status

Options: - --verbose: Show detailed status

Examples: 

ai-monitor status

ai-monitor status --verbose

ai-monitor status --json

suggestions

List and manage proactive suggestions

Usage: 

ai-monitor suggestions [OPTIONS]

Options: - --category: Filter by category - --resolve: Resolve suggestion by ID - --dismiss: Dismiss suggestion by ID - --cleanup: Cleanup old suggestions

Examples: 

ai-monitor suggestions

ai-monitor suggestions --category security

ai-monitor suggestions --resolve 1

ai-monitor suggestions --dismiss 2

ai-monitor suggestions --cleanup

ai-monitor suggestions --json

service

Manage the ai-monitor systemd service lifecycle

Usage: 

ai-monitor service <ACTION>

Options: - <ACTION>: install | uninstall | enable | disable | status

Examples: 

sudo ai-monitor service install

sudo ai-monitor service enable

ai-monitor service status

sudo ai-monitor service disable

sudo ai-monitor service uninstall

Operational Scenarios

Scenario-oriented workflows generated from the binary's built-in -e --json examples.

Scenario 1: Basic Usage

Basic monitoring operations

Step 1: Start the monitoring daemon with default settings

ai-monitor start
Expected Output: Monitor daemon started successfully

Step 2: Show current monitor status

ai-monitor status
Expected Output: Monitor status with active suggestions count

Step 3: List all active suggestions

ai-monitor suggestions
Expected Output: List of proactive suggestions

Step 4: Start daemon with JSON status output

ai-monitor start --json
Expected Output: JSON response with daemon process info

Note

Useful for automated service management

Step 5: Get monitor status as JSON

ai-monitor status --json
Expected Output: JSON with monitor state and suggestion counts

Note

Structured output for monitoring dashboards

Step 6: List all suggestions as JSON

ai-monitor suggestions --json
Expected Output: JSON array of active suggestions with metadata

Note

Structured output for programmatic consumption

Scenario 2: Advanced Configuration

Advanced monitoring and suggestion management

Step 1: Start with custom interval and security threshold

ai-monitor start --interval 60 --threshold 80
Expected Output: Monitor started with custom configuration

Note

Interval in seconds, threshold 1-100

Step 2: Start monitor as background daemon

ai-monitor start --daemon
Expected Output: Monitor daemon started in background

ai-monitor suggestions --category security
Expected Output: Filtered suggestions by category

ai-monitor suggestions --category network
Expected Output: Network category suggestions

Step 5: Mark suggestion as resolved

ai-monitor suggestions --resolve 1
Expected Output: Suggestion marked as resolved

Step 6: Get detailed status in JSON format

ai-monitor status --verbose --json
Expected Output: Comprehensive monitor status in JSON

Step 7: Start with all parameters and JSON output

ai-monitor start --interval 60 --threshold 80 --json
Expected Output: JSON with custom interval and threshold configuration

Note

60-second interval, 80% security threshold, structured output

Step 8: Security suggestions as JSON

ai-monitor suggestions --category security --json
Expected Output: JSON array of security-category suggestions

Note

Filter and format combined for automation

Scenario 3: Service Management

Manage the systemd daemon lifecycle

Step 1: Install service (if needed) and start as systemd daemon

sudo ai-monitor start --daemon
Expected Output: ai-monitor daemon started via systemd

Note

Requires root. Auto-installs the service file.

Step 2: Install the systemd service file

sudo ai-monitor service install
Expected Output: Service installed successfully

Step 3: Check the daemon status

ai-monitor service status
Expected Output: Service status with active/enabled state

Note

Does not require root

Step 4: Check daemon status as JSON

ai-monitor service status --json
Expected Output: JSON with service active/enabled state

Note

Structured output for monitoring scripts

Step 5: Stop, disable, and remove the service

sudo ai-monitor service uninstall
Expected Output: Service uninstalled successfully

Scenario 4: AI Tier Health Monitoring

Monitor health status of all 6 AI engine tiers

Step 1: Show health status of all AI tiers

ai-monitor status --json
Expected Output: JSON with per-tier availability and health

Note

Covers TF-IDF, ONNX, Mistral.rs, GenAI/Ollama, Legacy LLM, Claude tiers

Step 2: Security suggestions including AI tier recommendations

ai-monitor suggestions --category security --json
Expected Output: JSON with AI-informed security suggestions

Note

AI tiers can generate security recommendations via tool calling

Step 3: Monitor with AI tier health checks every 2 minutes

ai-monitor start --interval 120 --json
Expected Output: Daemon started with AI tier monitoring enabled

Note

Periodically checks Ollama, GGUF model, and Claude CLI availability

Scenario 5: Maintenance Operations

Cleanup and maintenance commands

Step 1: Cleanup old inactive suggestions

ai-monitor suggestions --cleanup
Expected Output: Count of cleaned up suggestions

Note

Removes suggestions older than 30 days

Step 2: Dismiss a suggestion without resolving

ai-monitor suggestions --dismiss 2
Expected Output: Suggestion marked as dismissed

Step 3: Show optimization suggestions

ai-monitor suggestions --category optimization
Expected Output: Performance and optimization suggestions

Step 4: Show recovery suggestions

ai-monitor suggestions --category recovery
Expected Output: System recovery and repair suggestions

Scenario 6: ONNX Classifier & Policy Monitoring

Monitor ONNX intent classifier and AI policy file health

Step 1: Check ONNX intent classifier health

ai-monitor status --json
Expected Output: JSON including ONNX classifier model status

Note

Verifies kodachi-intent-classifier.onnx is loadable

Step 2: Check AI policy file integrity

ai-monitor status --json
Expected Output: JSON including policy file signature verification

Note

Verifies ai-policy.json exists and signature is valid

Step 3: Show ONNX vs LLM routing statistics

ai-monitor status --json
Expected Output: JSON with fast-path (ONNX) vs slow-path (LLM) breakdown

Note

Shows percentage of queries routed via fast path

Environment Variables

Variable Description Default Values
RUST_LOG Set logging level info error
NO_COLOR Disable all colored output when set unset 1

Exit Codes

Code Description
1 General error
4 Network error
5 File not found
3 Permission denied
2 Invalid arguments
0 Success