Premium technical knowledge hub visual for Jarvis documentation, workflows, privacy modes, model routing, and field notes.
Neural Command Manual v1.0.0

Master Jarvis AI Assistant.
Command the whole system.

From your first query to advanced desktop automation, model routing, mobile control, memory, privacy modes, and real agent workflows.

01Commands

Essential Commands Reference

Every powerful Jarvis interaction starts with the right command. These patterns cover 90% of daily usage.

Basic Queries

$jarvis "your question or task"
# Ask anything — Jarvis routes to the best model
$jarvis "explain this error: [paste error]"
$jarvis "summarize my git log from today"

Model Selection via Prefix

# Prefix overrides the default model
$jarvis "claude: write unit tests for auth.py"
$jarvis "gpt: brainstorm product names"
$jarvis "groq: quick translation to Spanish"
$jarvis "ollama: explain this — keep it local"

Interface Modes

$jarvis
# Interactive Rich terminal REPL
$jarvis --web
# Launch web dashboard on :3001
# Or use the Desktop App (Microsoft Store)

Privacy Overrides

# Set mode for this session only
$JARVIS_PRIVACY_MODE=STRICT jarvis
$JARVIS_PRIVACY_MODE=GUARDED jarvis
# Or set permanently in .env
$JARVIS_PRIVACY_MODE=RELAXED jarvis --web

Memory & Recall

$jarvis "what did I work on yesterday?"
$jarvis "recall my notes about the auth refactor"
$jarvis "summarize last week conversations"
# Searches PostgreSQL full-text history

Tool-Specific Queries

$jarvis "create a Jira ticket for the auth TODO"
$jarvis "what Docker containers are running?"
$jarvis "run diagnostics on the API server"
$jarvis "reply to my last WhatsApp from [name]"

Pro Tip — Natural Language is Enough

Jarvis understands intent, not just keywords. You do not need to know tool names. Say "check if my API is down and open a ticket if it is"Jarvisselects the right tools, runs them in parallel, and chains the results automatically.

02Workflows

Power Workflows for Real Work

Complete end-to-end workflows that show Jarvis working autonomously — not just answering questions.

Developer Daily Workflow

Morning standup to end of day

1

Morning Standup Prep

Ask Jarvis to summarize yesterday's commits so you can report progress without digging through git logs.

jarvis "summarize my git commits from yesterday with key changes"
2

Automated Ticket Creation

Jarvis scans your codebase for TODO comments and creates properly formatted Jira tickets automatically.

jarvis "find all TODO comments in src/ and create Jira tickets for each"
3

Intelligent Debugging

Paste an error and Jarvis reads the relevant files, traces the stack, and suggests a targeted fix.

jarvis "debug this: [paste error] — check the auth middleware and recent changes"
4

End-of-Day Summary

Generate a readable summary of your day, commits, and open issues for the next session.

jarvis "write a summary of what I shipped today and what is still open"
🖧

Infrastructure & Ops Workflow

Monitor, diagnose, remediate

1

Natural Language Monitoring

Query container health, resource usage, and service status without memorising Docker or kubectl commands.

jarvis "show running containers and flag any using more than 80% CPU"
2

Network Intelligence

Check Tailscale mesh status, identify offline nodes, and get explanations of network anomalies.

jarvis "check Tailscale — which nodes are offline and when did they go down?"
3

Automated Diagnostics

Run a full diagnostic suite in one command — Jarvis runs tools in parallel and aggregates findings.

jarvis "run full diagnostics on the API: logs, health check, db connections, latency"
4

Runbook Execution

Jarvis remembers runbooks from past conversations. Reference them by name to execute remediation.

jarvis "the API is throwing 503s — follow the standard restart runbook"
📊

Research & Analysis Workflow

Research, synthesize, report

1

Web Research

Jarvis searches the web, scrapes relevant pages, and synthesizes findings — not just a list of links.

jarvis "research the top 5 approaches to rate limiting APIs and compare them"
2

Cross-Session Recall

Query your own conversation history to recall decisions and research from months ago.

jarvis "what did I decide about the database schema for user sessions?"
3

Multi-Model Validation

Get answers validated across multiple LLMs by routing the same question to different providers.

jarvis "ask both claude and gpt-4o: is this SQL injection-safe? [paste code]"
4

Report Generation

Combine filesystem data, web research, and conversation history into a structured report.

jarvis "generate a weekly engineering report from my git history and open Jira tickets"
03Desktop App

The Full Jarvis Desktop Experience

The Windows Desktop App is the recommended way to use Jarvis — no terminal needed, auto-updates, always available.

Install from Microsoft Store

One click install from the Microsoft Store. Auto-updates when new versions are released. No terminal, no setup — just install and run.

Download from Microsoft Store

Store ID: 9ND65V74RVTB

What the Desktop App Includes

🖥Full Jarvis interface — chat, tools, memory
🔄Auto-update — always on the latest version
🎙Voice mode — Whisper STT + Kokoro TTS built in
🌐Built-in web dashboard at localhost:3001
🔒Privacy guard — STRICT mode by default
💾Local memory — your data stays on your machine
DESKTOP APP — FIRST LAUNCH
1

Install

Download and install from the Microsoft Store. Launch Jarvis.

2

Add API Key

Go to Settings and add your preferred LLM API key. Groq is free to start.

3

Set Privacy Mode

Choose STRICT (local only), GUARDED (cloud + redaction), or RELAXED.

4

Start Asking

Type or speak your first query. Jarvis routes it, runs tools, responds.

Using Jarvis via Terminal (Advanced)

$jarvis
# Rich terminal REPL — fastest raw interface
$jarvis --web
# Launch web dashboard on localhost:3001

The CLI is ideal for power users who live in the terminal. The Desktop App and CLI share the same agent, tools, memory, and settings.

04Auto-Reply Engine

WhatsApp & Messenger Automation

Let Jarvis manage your messages intelligently — context-aware replies, scheduling, and custom rules.

WhatsApp Auto-Reply

# Enable from Settings in the Desktop App
# Settings → Messaging → WhatsApp
# Or via terminal command
$jarvis "enable WhatsApp auto-reply: I am busy, will reply later"
$jarvis "set auto-reply schedule: 9pm to 9am weekdays"

Messenger Auto-Reply

# Messenger bridge via WAHA integration
$jarvis "enable Messenger auto-reply"
$jarvis "reply to [contact] last Messenger message"
$jarvis "summarize unread Messenger messages from today"
INTELLIGENT AUTO-REPLY CAPABILITIES

Context-Aware

Reads message content and generates a relevant reply — not a generic canned response.

Scheduled

Set active hours. Auto-reply fires only during off-hours or when you mark yourself as busy.

Whitelist Control

Control which contacts trigger auto-reply. VIPs always get through, others get the template.

Manual Message Management

$jarvis "show all unread WhatsApp messages"
$jarvis "reply to [name]: I will call you in 30 minutes"
$jarvis "forward the message from [name] to my notes"
$jarvis "create a Jira ticket from [name] WhatsApp request"
05LLM Routing

Route Every Query to the Right Model

Jarvis automatically selects the best provider — or you can override with a prefix. No config files needed.

PREFIXPROVIDER
claude-*Anthropic
claude-code-*Claude Code CLI
gpt-*OpenAI
gemini*Google
groq/*Groq
ollama/*Ollama
cursor*Cursor Agent

Routing in Practice

# Default — Jarvis picks the best model
$jarvis "what is the time complexity of quicksort?"
# Force a specific model with prefix
$jarvis "groq: translate this paragraph quickly"
$jarvis "ollama/llama3: keep this completely local"

Set Your Default Model

# In .env file
$JARVIS_DEFAULT_MODEL=claude-code-sonnet
# Or per-session override
$JARVIS_DEFAULT_MODEL=gpt-4o jarvis
# Current default: qwen3-coder-next:cloud
06Profile & Memory

Personalize Jarvis to Know You

The profile system injects your context into every conversation. Memory means Jarvis never forgets a decision.

Your Profile (~/.jarvis/profile.json)

Configure from the Desktop App or web dashboard: Settings → Profile

name:How Jarvis addresses you
role:Informs technical depth and framing
projects:Active project context injected per query
instructions:Permanent preferences (e.g. "use TypeScript")
memories:Saved behavioral hints from past sessions

How Memory Works

Every conversation is saved to PostgreSQL with full-text search indexing.

Redis caches recent context for instant recall within a session.

Tool success/failure rates and error→fix mappings tracked in smart_memory.db.

Your profile is injected into every prompt with a 60-second cache — zero overhead.

Memory Commands

$jarvis "save this to memory: I prefer Redis for caching"
$jarvis "what decisions have I made about the auth system?"
$jarvis "show me all conversations about the landing page"
$jarvis "forget the note about using MySQL"
07Privacy Modes

Configure Your Privacy Level

Three modes from fully local to cloud-optimised. Every mode is explicit — nothing surprises you.

🔒STRICTLocal-First. Zero Cloud.

All LLM calls go to local Ollama models only. No data leaves your device. Fernet encryption at rest. Ideal for sensitive codebases and regulated environments.

JARVIS_PRIVACY_MODE=STRICT
JARVIS_DEFAULT_MODEL=ollama/llama3
# Ensure Ollama is running: ollama serve
🛡GUARDEDCloud with Auto-Redaction. (Recommended)

Cloud LLMs allowed but PrivacyGuard strips API keys, passwords, and PII before any send. Every external call is audit-logged. Best balance of power and privacy.

JARVIS_PRIVACY_MODE=GUARDED
JARVIS_DEFAULT_MODEL=claude-sonnet-4
# Audit: ~/.jarvis/security_audit.db
RELAXEDMaximum Performance. Dev Only.

No interception layer. All providers available at full throughput. Use only for development work with non-sensitive data.

JARVIS_PRIVACY_MODE=RELAXED
# WARNING: no secret redaction active
# Never use with production credentials
08Pro Tips

8 Patterns That 10x Your Productivity

These are not obvious from the docs. They come from using Jarvis at scale across thousands of queries.

01

Chain Commands Naturally

Jarvis understands "and then" instructions. One message can trigger a 5-step chain: analyze → create ticket → notify on Slack → update status → summarize.

jarvis "review my PR, create a Jira for each issue, and message me the summary on WhatsApp"
02

Be Specific About Output

Tell Jarvis exactly what format you want. "In a markdown table", "as a bash script", "in 3 bullet points" — it follows formatting instructions precisely.

jarvis "list open Docker issues as a markdown table with a severity column"
03

Reference Files Directly

Jarvis can read any file on your system. Reference them by path and it will read, analyze, and act on the content automatically.

jarvis "review src/auth/login.py and suggest security improvements"
04

Use Parallel Execution Explicitly

When you need multiple independent operations, say "simultaneously" — Jarvis uses asyncio.gather() and returns all results at once.

jarvis "simultaneously: check Docker, ping the API, and scan for TODO comments"
05

Build on Previous Responses

Jarvis retains conversation context. Follow up naturally in the REPL. "Make it shorter", "Now do the same for the API module", "Use Redis instead."

jarvis "now apply the same refactor to the other 3 files in that directory"
06

Voice Mode in the Desktop App

Enable voice mode in the Desktop App settings. Dictate queries while reading code, hear results spoken back — no keyboard interruption needed.

# Enable in Desktop App: Settings → Voice → Enable Whisper
07

Project Context Auto-Loading

Register your projects once and Jarvis automatically injects the right context based on your query — no manual setup per conversation.

jarvis "what are the open issues in this project?" # knows your active project
08

Ask Why It Did What It Did

If Jarvis does something unexpected, just ask. "Why did you use that tool?", "What data did you send?" — it explains its reasoning transparently.

jarvis "explain what tools you just called and why"

READY TO START

You now know Jarvis.
Go build something.

Install in 3 minutes. Run your first intelligent command. Experience the difference between a chatbot and a real AI system.