Binary reference

ai-monitor

Proactive system monitoring daemon with anomaly detection and suggestions

Version9.8.4Size4.0MBAuthorWarith Al MaawaliLicenseProprietaryWebsitehttps://www.digi77.com

File Information

Property	Value
Binary Name	ai-monitor
Version	9.8.4
Build Date	Not disclosed
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	2026-07-11T18:16:29Z
Binary Timestamp	Unknown
JSON Data	View Raw JSON

SHA256 Checksum

67751148aad964f29105bd1c77e6f5bfa516e9dc20fc1a92bc9baced0a0a5890

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)
`--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\|warn\|info\|debug)
`--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

`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\|warn\|info\|debug\|trace
`NO_COLOR`	Disable all colored output when set	unset	1\|true\|yes (any value disables color)

Exit Codes

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

ai-monitor

Proactive system monitoring daemon with anomaly detection and suggestions

File Information

SHA256 Checksum

Features

Security Features

System Requirements

Global Options

Commands

Commands

start

status

suggestions

service

Operational Scenarios

Scenario 1: Basic Usage

Step 1: Start the monitoring daemon with default settings

Step 2: Show current monitor status

Step 3: List all active suggestions

Step 4: Start daemon with JSON status output

Step 5: Get monitor status as JSON

Step 6: List all suggestions as JSON

Scenario 2: Advanced Configuration

Step 1: Start with custom interval and security threshold

Step 2: Start monitor as background daemon

Step 3: List security-related suggestions only

Step 4: Show network-related suggestions

Step 5: Mark suggestion as resolved

Step 6: Get detailed status in JSON format

Step 7: Start with all parameters and JSON output

Step 8: Security suggestions as JSON

Scenario 3: Service Management

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

Step 2: Install the systemd service file

Step 3: Check the daemon status

Step 4: Check daemon status as JSON

Step 5: Stop, disable, and remove the service

Scenario 4: AI Tier Health Monitoring

Step 1: Show health status of all AI tiers

Step 2: Security suggestions including AI tier recommendations

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

Scenario 5: Maintenance Operations

Step 1: Cleanup old inactive suggestions

Step 2: Dismiss a suggestion without resolving

Step 3: Show optimization suggestions

Step 4: Show recovery suggestions

Scenario 6: ONNX Classifier & Policy Monitoring

Step 1: Check ONNX intent classifier health

Step 2: Check AI policy file integrity

Step 3: Show ONNX vs LLM routing statistics

Environment Variables

Exit Codes

`start`

`status`

`suggestions`

`service`