At a pivotal moment when AI is evolving from “being able to answer” to “being able to execute,” a new technical dividing line is emerging across the industry: how to truly turn complex agent capabilities into services that are usable, controllable, and tradable. CloudClaw, a project that has recently attracted attention, has not chosen to continue competing at the model layer. Instead, it starts from system architecture and proposes a layered technical framework centered on the “serviceization of agents.”

CloudClaw’s overall architecture presents a clear bottom-up layered structure. This is not merely a conventional software stack, but a technical pathway that progressively transforms AI capabilities into product capabilities, then into market capabilities, and ultimately into enterprise-grade service capabilities.

At the foundation layer, the system does not attempt to replace existing agent frameworks. Instead, it connects to the current ecosystem through a compatibility mechanism. In essence, this layer functions as a runtime adaptation layer responsible for uniformly integrating agent capabilities from different sources, including task execution logic, skill modules, and tool-calling interfaces. What the system accomplishes here is not computation itself, but capability abstraction: it converts previously fragmented agent instances into standardized execution units that can be orchestrated and scheduled. In terms of code logic, this process resembles building a dynamic router. When a task enters the system, the appropriate agent execution path is selected through contextual analysis, rather than being statically bound to a single model or instance.

On top of this, CloudClaw introduces a highly engineering-oriented training and evaluation layer. Unlike traditional AI systems, “training” here no longer refers to optimizing model parameters. Instead, it refers to the construction of a fully engineered workflow around task execution. By describing tasks in a structured way and combining prompt design, tool orchestration, and execution-path design, the system enables agents to operate reliably within specific scenarios. The core logic of this layer is much closer to continuous integration in software engineering: execution quality is improved through testing, regression, and version control, rather than relying solely on the accuracy of a single inference. In this sense, CloudClaw turns AI capability into an iterative software behavior.

Once execution capability becomes stable, the system begins to introduce constraint mechanisms, which is exactly the role of the security and isolation layer. Unlike traditional applications, the risks in agent systems come from execution itself, so CloudClaw embeds security design directly into the architecture. Through multi-tenant isolation, different users and tasks operate in independent contexts. At the same time, least-privilege controls restrict the range of tools each agent can access. For credential handling, the system uses a segmented management strategy so that sensitive information is never directly exposed to execution logic, thereby reducing the risk of leakage across complex call chains. More importantly, the system continuously records the execution chain during runtime, ensuring that every task is traceable from input to output. This observable execution mechanism gives AI systems, for the first time, an audit capability similar to that of traditional backend services.

After capability packaging and security controls are in place, CloudClaw does not stop at the technical layer. It goes a step further by building a market and distribution layer. The emergence of this layer transforms the system from a collection of tools into a service marketplace. At this level, all agent capabilities are standardized and described in a unified way, and supply-demand matching is achieved through search, recommendation, and ranking mechanisms. Users no longer need to face the complexity of model selection; instead, they can directly invoke service outcomes based on task requirements. At the same time, the system continuously adjusts service weights through ratings and feedback, allowing the market structure to optimize itself over time. This design gives AI capability, for the first time, a circulation property similar to that of a commodity.

As usage and invocation begin to occur, the system moves into the settlement and economics layer. At this stage, each task execution is translated into a unit of value flow. The system automatically completes fee settlement and distributes revenue between capability providers and the platform itself according to defined rules. This is not merely a payment process, but also an implementation of incentive mechanisms. Since the supply side must maintain service visibility through staking, while the demand side generates consumption through real usage, the system gradually forms a dynamic equilibrium structure: the more frequently services are used, the more stable the supply becomes, and the stronger the overall platform value grows.

At the top of the stack, CloudClaw builds enterprise API capabilities, enabling the entire system to expose extensible external interfaces. This layer is not simply about opening up API calls. Instead, it integrates permission control, call logging, quota management, and organization-level access capabilities, allowing enterprises to use agent services in a controlled environment. In other words, the role of this layer is to transform AI capabilities originally aimed at individual users into foundational components that can be embedded into enterprise systems.

Taken as a whole, CloudClaw’s six-layer technical structure effectively completes a full technical translation process: at the bottom lies agent capability; in the middle are engineering encapsulation and security controls; at the top are market mechanisms and value flows; and the final external manifestation is enterprise-grade service capability. The significance of this structure lies in the fact that it integrates previously fragmented AI capabilities into a system with operational logic, governance mechanisms, and an economic model.

Even more noteworthy is that this architecture does not depend on any single model or technical path. Instead, through layered design, it achieves adaptability to ongoing technological change. The bottom layer can continue to evolve along with agent frameworks, while the upper-layer service logic and market structure remain stable. This decoupled design makes CloudClaw closer to infrastructure than to a single product.

At a time when AI is increasingly becoming a real productivity tool, relying solely on model capability is no longer enough to build long-term competitiveness. The path demonstrated by CloudClaw may suggest that the next critical step lies not in “more powerful AI,” but in “more usable AI.” By transforming complex capabilities into standardized services and orchestrating and distributing them within a secure and institutional framework, this kind of system is redefining how AI is put into practice.

Abstract. CloudClaw delivers tool-enabled AI agents as market-grade service units rather than as standalone chat bots. This shifts the security problem from ordinary account and API protection to tenant-safe execution, tool mediation, credential segmentation, runtime policy enforcement, and auditable settlement. This article presents the CloudClaw security control plane and tenant isolation design, including identity-scoped execution cells, least-privilege policy resolution, credential brokerage, tool allowlisting, append-only audit streams, and risk-aware circuit breaking. The architecture is designed to support both multi-tenant consumer workloads and enterprise-grade isolated deployments.

Keywords: security control plane, tenant isolation, zero trust, tool-enabled agents, credential brokerage, policy engine, audit bus, circuit breaker

Figure 1. CloudClaw zero-trust security architecture with control-plane / execution-plane separation.

1. Introduction

CloudClaw does not merely host conversational AI. It executes service-grade AI agents—called cloud lobsters—that can call tools, access knowledge assets, compose outputs, and trigger external actions on behalf of users or enterprises. As a result, the platform's primary security challenge is not limited to user authentication or API hardening. Instead, it must guarantee that every invocation is constrained by tenant identity, permission scope, credential boundaries, runtime policy, and auditable execution semantics.

In a shared AI-agent marketplace, the threat model is fundamentally different from that of a conventional web application. A single unsafe skill, an over-privileged tool grant, a leaked credential, or a contaminated memory store may lead to cross-tenant disclosure, unauthorized actions, or billing disputes. CloudClaw therefore adopts a security-control-plane design in which security decisions are externalized from the agent runtime and enforced before, during, and after every task.

The technical objective is twofold: first, to preserve strict isolation across mutually untrusted tenants; second, to maintain the flexibility needed by market-grade AI services, including dynamic tool use, multi-step orchestration, policy-controlled automation, and traceable settlement. The sections below describe how these properties are achieved.

2. Threat Model and Design Principles

CloudClaw assumes that tenants, users, skills, tools, and third-party endpoints cannot be treated as uniformly trusted. The platform explicitly models the following threat classes: (i) cross-tenant data contamination; (ii) prompt- or tool-mediated privilege escalation; (iii) credential exfiltration from runtime contexts; (iv) unsafe or malicious skills; (v) memory leakage between sessions; (vi) unauthorized external actions; and (vii) non-repudiable billing or settlement disputes.

To address these risks, the architecture follows five design principles:

· Tenant-bound execution: Every invocation is resolved to a tenant-specific security context before any agent logic starts.

· Least-privilege by default: Agents receive only the minimum tool, data, and network capabilities required for the declared service scope.

· Credentialless runtime: The agent never receives raw long-lived secrets; it obtains only scoped ephemeral grants via a broker.

· Mediated side effects: External tool calls pass through a Tool Proxy that enforces allowlists, schema validation, and risk checkpoints.

· Audit-first enforcement: Every significant decision, tool call, and state transition is logged as signed append-only evidence.

3. Security Control Plane Architecture

The CloudClaw security control plane is logically separate from the execution plane. The control plane owns identity resolution, tenant directories, role and attribute policies, capability issuance, risk scoring, alerting, and human escalation. The execution plane hosts isolated execution cells that run agent workloads under the constraints issued by the control plane.

At a high level, the architecture consists of the following components:

· Identity and Tenant Manager: resolves user, tenant, role, workspace, and service plan into a canonical security context.

· Policy and Capability Service: evaluates static and dynamic policies and issues short-lived capability tickets.

· Execution Cells: sandboxed runtime environments dedicated to a tenant or risk class.

· Secrets Vault and Credential Broker: stores long-lived secrets but releases only ephemeral scoped credentials.

· Tool Proxy: mediates all external actions, validates payloads, and records the full execution trace.

· Audit Bus: receives signed append-only events from runtimes and proxies.

· Risk Engine: scores anomalous behavior and can downgrade, block, or quarantine a service.

· Security Operations Layer: performs monitoring, forensics, policy overrides, and incident response.

3.1 Canonical Security Context

Every inbound request is normalized into a canonical context object. This object is attached to all subsequent operations, including memory retrieval, policy checks, tool calls, logging, and settlement.

4. Tenant Isolation Model

CloudClaw tenant isolation is intentionally multi-layered. It is not implemented as a single tenant_id column in application tables. Instead, isolation is enforced across identity, storage, memory, runtime, network, and audit paths.

4.1 Identity Isolation

The identity layer resolves users into tenant-scoped roles using RBAC and ABAC. Role assignments are never interpreted globally. A user may hold an 'analyst' role in one tenant but have no permissions in another. Every permission check is therefore evaluated against the tuple (tenant_id, user_id, role, agent_id, resource).

4.2 Data Isolation

CloudClaw supports both logical isolation and strong physical isolation. Consumer tenants may use row-level security, namespaced object storage prefixes, and tenant-scoped vector indexes. Enterprise deployments may upgrade to dedicated databases, isolated object storage, separate vector stores, and private network segments.

4.3 Memory Isolation

AI-agent platforms introduce a memory-specific risk: semantic recall may surface another tenant's data even when application rows are properly filtered. To prevent this, CloudClaw shards memory by tenant, user, agent, and workspace. Persistent memory and retrieval indexes are therefore scoped to a composite boundary rather than to a globally shared corpus.

4.4 Runtime Isolation

The runtime scheduler does not execute all invocations inside a single shared agent process. Instead, tasks are placed into pools based on risk and trust requirements. Low-risk requests may run in shared sandboxes; tool-enabled tasks use mediated runners; credential-bearing or enterprise-sensitive workloads are placed in dedicated execution cells; high-sensitivity enterprise tenants can be pinned to private network segments or dedicated hosts.

5. Least-Privilege Capability Resolution

CloudClaw requires each cloud-lobster service unit to declare an execution manifest. The manifest defines the tool set, data domains, network egress allowlist, user-confirmation requirements, timeout budgets, and audit level. The policy engine evaluates the manifest against tenant policy and live risk signals before granting capabilities.

A capability ticket is then derived from the manifest and the security context. Capability tickets are short-lived, non-transferable, tenant-bound, and trace-linked. They are validated by the Tool Proxy and are not interpreted as general bearer privileges.

5.1 Authorization Logic

By externalizing authorization into a policy service, CloudClaw avoids trusting prompt content or agent self-discipline as the ultimate security boundary. The runtime can only perform actions that have already been reduced to explicit, signed capability decisions.

Figure 2. Request lifecycle with policy resolution, execution mediation, audit emission, and risk-aware enforcement.

6. Credential Segmentation and Tool Proxy Design

Long-lived secrets are never injected directly into the agent prompt, memory, or execution context. Instead, CloudClaw uses a Credential Broker to translate static secrets from a vault into ephemeral, scope-constrained grants. This pattern eliminates raw secret exposure from agent-visible contexts and sharply reduces the blast radius of prompt injection or runtime compromise.

All tool effects pass through a Tool Proxy rather than reaching external APIs directly. The proxy verifies that the requested tool is allowlisted, that the payload conforms to a declared schema, that the egress destination is permitted, and that user confirmation is present when the action is classified as high risk.

This design makes side effects explicit and reviewable. It also ensures that agents remain capability consumers rather than capability owners.

7. Auditability, Metering, and Dispute Readiness

CloudClaw treats logging as evidence rather than as operational exhaust. The audit bus receives signed, append-only events from the execution cell, Tool Proxy, policy service, and metering layer. The goal is to reconstruct the exact chain of decisions that led to a tool call, result emission, or billing event.

Because CloudClaw is both an execution platform and a market, audit trails must serve three functions at once: security forensics, service quality review, and settlement evidence. A clean trace therefore links security decisions to billing units, replayable execution state, and, where necessary, human intervention records.

8. Runtime Risk Engine and Circuit Breaking

The Risk Engine continuously evaluates execution context, user history, tool class, action class, payload characteristics, anomaly signatures, and external response patterns. It computes a runtime score that can downgrade permissions, require user confirmation, freeze settlement, suspend sessions, or quarantine an agent.

A critical property of this design is that risk controls remain external to the agent's reasoning loop. The model may suggest or request an action, but the final decision authority resides in the control plane. This sharply reduces the probability that an unsafe tool invocation will succeed due to prompt manipulation alone.

9. Technical Advantages and Differentiators

CloudClaw's security architecture differs from conventional SaaS hardening in several important ways.

10. Enterprise Isolation Tiers

CloudClaw supports multiple deployment tiers so that isolation strength can match business sensitivity and regulatory pressure.

11. Conclusion

CloudClaw answers a central systems question for AI-agent platforms: how can a service safely allow autonomous tool use without turning shared infrastructure into a cross-tenant risk amplifier? The answer is to build security as a control plane rather than as an afterthought inside prompts or business logic.

By combining canonical tenant contexts, least-privilege capability tickets, credential brokerage, mediated tool execution, append-only audit streams, and risk-aware circuit breaking, CloudClaw turns AI-agent execution into a governable, enterprise-compatible service fabric. Its main technical distinction is that isolation, policy, auditability, and settlement are designed as one coherent system rather than as loosely coupled add-ons.

For consumer workloads, this architecture reduces the probability of cross-tenant leakage and unsafe automation. For enterprise customers, it provides the boundary clarity, observability, and deployment flexibility required for high-sensitivity adoption. For the broader CloudClaw marketplace, it establishes a credible trust foundation on which service ranking, billing, governance, and long-term ecosystem growth can operate.

Appendix A. Minimal Execution Manifest

Appendix B. Reference Implementation Notes

A production deployment would typically implement the control plane as a set of independently scalable services: identity resolver, policy engine, credential broker, audit bus, and risk engine. Execution cells may run as isolated worker pools or dedicated micro-VMs. Object storage, vector indexes, and relational stores should all enforce tenant scoping. The exact infrastructure substrate may vary, but the boundary model described in this document should remain invariant.

End of document.

I. Project Overview

Cloud Claw is dedicated to building the "Digital Labor Dispatch Center" for the Web3 and AI era. Leveraging the powerful OpenClaw open-source technical foundation, we encapsulate complex AI model training and computational power invocation into ready-to-use, freely tradable cloud-based AI Agent services.

We provide more than just a technical framework; we have established a bilateral service marketplace connecting "top-tier global AI developers" with "massive C-end/B-end users." Our mission is to make accessing premium AI capabilities as simple as "ordering takeout" or "renting a cloud server."

II. Industry Pain Points: Bridging the AI Implementation Gap

As Large Language Models (LLMs) evolve into autonomous Agents, the industry faces three major hurdles preventing large-scale commercialization:

1. Technical Barriers for Individuals & SMEs: 99% of users and small-to-medium enterprises lack the technical ability to fine-tune models, build complex workflows, and sustain high computational costs. This leaves top-tier AI as a "toy" for a small group of geeks.

2. Commercial Disconnect for Top Developers: Excellent AI trainers and geek studios lack a standardized infrastructure to convert "model capabilities" into "sustained commercial revenue," often leaving them in a state of uncompensated passion projects.

3. Lack of Trust and Delivery Hubs: In globalized cross-border collaboration, ensuring computational cost transparency, data privacy, and service delivery results is difficult without a consensus-based system.

III. Core Business Engine: Claw Marketplace

To solve these pain points, we launched our flagship product line: the Claw Marketplace. This is a globally open AI-Agent-as-a-Service (AaaS) platform:

• For the Supply Side (Professional Trainers/Studios): We provide a full suite of API interfaces from model deployment to service listing. Developers can list their fine-tuned, professional-grade "Cloud Claw" on the market to serve global users and receive transparent, real-time commercial revenue sharing.

• For the Demand Side (Users/Enterprise Clients): Moving away from complex code and prompt engineering, users simply search for their required application scenario and can purchase or invoke professional cloud AI services with a single click.

IV. Commercial Moat: The Pioneering "Three-Layer Synergy Architecture"

Unlike traditional tech firms or loosely organized decentralized projects, Cloud Claw adopts a "Three-Layer Synergy Architecture" with clear divisions of rights and responsibilities:

1. Technical Foundation: OpenClaw Foundation (Upstream Open Source)

   • Role: The source of technology and industry credibility.

   • Responsibility: Focuses on the continuous iteration of the underlying framework, establishing industry-grade interface standards, and security boundaries. It remains commercially neutral to ensure the purity of the open-source geek spirit.

2. Governance Hub: CLAWDAO (Ecosystem Initiator)

   • Role: The project’s "Supreme Council" and resource allocation center.

   • Responsibility: Builds community consensus, manages treasury funds, and handles proposals/voting for major development directions to ensure long-term ecosystem governance.

3. Commercial Execution: CLAW Labs (Independent Operating Entity)

   • Role: The commercial "Spearhead" focused on operations and revenue.

   • Responsibility: Handles the daily operation of the Claw Marketplace, Business Development (BD) for major enterprise clients, customized B2B API delivery, and global legal compliance/risk management.

V. Core Application Scenarios & Delivery Capabilities

The first batch of commercially available "Cloud Claws" targets high-frequency scenarios with deep pain points and strong cash flow:

• Web3 Trading & Financial Assistance: 24/7 on-chain anomaly monitoring, automated generation of complex research reports, quantitative trading signal filtering, and risk alerts.

• Cross-border E-commerce & Automated Marketing: Automatic generation of viral product visuals/copy, multi-language 24/7 intelligent customer service, and automated distribution/growth hacking for social media matrices.

• Enterprise Productivity: Knowledge Base Agents deeply integrated with internal corporate databases to replace tedious traditional OA (Office Automation) processes.

VI. Vision & Future

Cloud Claw is more than just a tool platform; our ultimate vision is to build the infrastructure for the next generation of the Internet.

In the future, whether you need a precise investment strategy or a tireless automated operations team, you will find the most professional "Digital Employees" within the Cloud Claw network. We are reshaping the commercial value of AI compute and leading humanity into the Great Age of Digital Labor Discovery.

On this final day, we will:

• Review the complete 7-day journey

• Unlock advanced techniques: custom skills, multi-device, API integration

• Cover the security checklist you need to follow

• Look ahead to the future of AI assistants

• Give you a roadmap for continued growth

Congratulations, Graduate

Let's review what you accomplished in these seven days:

What you have now isn't a chatbot—it's a digital partner working alongside you.

Today we're not configuring anything new. Today we'll discuss three things: how to make it stronger, how to make it safer, and where all this is heading.

Advanced Level 1: Write Your Own Skill

Community Skills not enough? Write your own.

Don't worry, writing a Skill is simpler than you think—essentially it's just writing a Markdown file telling the AI "you can now do this thing, here's how."

Minimal Skill Example

MyClaw Cloud: Create new skill files through the Dashboard file editor. Navigate to your instance's skills directory and create a new folder with a SKILL.md inside it. Your assistant will automatically pick up the new skill.

Self-hosted: Create the skill file in your skills directory:

mkdir -p ~/clawd/skills/weather
nano ~/clawd/skills/weather/SKILL.md

Here's a complete minimal skill:

# Weather Query Skill

## Capability
You can query weather information for any city.

## Usage
Call the wttr.in API to get weather:

curl "wttr.in/CityName?format=3"

Example:
curl "wttr.in/NewYork?format=3"

## Output Format
Tell the user the current weather in concise language, including temperature and conditions.

That's it. No complex SDK, no registration process, one Markdown file is one Skill.

After saving, tell your assistant "What's the weather like in New York today"—it will read this Skill, call the wttr.in API, and return weather information.

Skill Development Principles

• SKILL.md is the core: Write clearly what it can do, how to do it, output format

• Keep it simple: One Skill does one thing, does it well

• Error handling: Write in SKILL.md "what to do if it fails"

• Security notes: For Skills involving sensitive operations, note that confirmation is needed

Advanced Level 2: Multi-Device Collaboration (Nodes)

Your assistant currently runs on one server. But what if it could simultaneously "see" your phone's camera, "control" your computer's browser, "access" your home smart devices?

That's the Nodes system.

What Are Nodes?

A Node is a lightweight client installed on other devices that connects to your main OpenClaw instance, letting your assistant:

• Phone Node: Take photos (front/back camera), get location, send system notifications

• Computer Node: Screenshot, screen record, control browser

• Raspberry Pi Node: Control smart home devices

Example Scenarios

Scenario 1: Remote Viewing You're traveling for business, tell your assistant: "Show me what's on my office computer screen"—the office computer with Node installed automatically takes a screenshot and sends it to you.

Scenario 2: Phone Collaboration Assistant pops up a notification on your phone: "You have a meeting at 3 PM, should I open the meeting link for you?"—you tap confirm, it opens directly on your phone.

Scenario 3: Smart Home "Turn off the living room lights" — Assistant controls HomeAssistant through Raspberry Pi Node — Lights off.

How to Set Up

MyClaw Cloud: Your cloud instance serves as the central hub. Install the Node client on any additional device you want to connect:

curl -fsSL https://openclaw.ai/install.sh | bash

For phones, search OpenClaw in the App Store. After installation, approve the pairing from your MyClaw Dashboard's Nodes panel.

Self-hosted: Install the Node client on the device you want to connect:

curl -fsSL https://openclaw.ai/install.sh | bash

For phones, search OpenClaw in the App Store. After installation, approve the pairing request on your main server:

openclaw nodes approve <device-name>

Once paired, you can issue cross-device commands directly in Telegram.

Advanced Level 3: Security Checklist

Your AI assistant can now access your emails, calendar, files, browser, and possibly your phone and computer. Security isn't optional—it's mandatory.

Here's a complete security checklist:

Server Security

MyClaw Cloud: Server-level security is handled for you — isolated instances, encrypted storage, automated updates. You still need to secure your own credentials and behavioral rules.

Self-hosted:

• SSH uses key authentication, password login disabled

• Firewall enabled, only necessary ports exposed (22, 443)

• System updated regularly: sudo apt update && sudo apt upgrade

• Run OpenClaw as non-root user

• Enable fail2ban to prevent brute force attacks

API Key Security

• All API Keys stored in environment variables or .env files

• .env file added to .gitignore

• Keys rotated regularly (recommend every 3 months)

• Different keys for different services

• API usage limits set to prevent runaway costs

Data Security

• OAuth Token file permissions set to 600

• Regular backup of working directory

• Sensitive files not committed to Git

• Clear understanding of what data assistant can and cannot access

Behavioral Security

• SOUL.md has clear "absolutely do not" list

• External messages (email, social media) must be confirmed

• Destructive operations (delete files, modify configs) must be confirmed

• Don't leak private info in group chats

• Use trash instead of rm (recoverable is better than unrecoverable)

Cost Control

• Set monthly API budget limit

• Monitor token usage

• Heartbeat interval not too short (30 minutes is enough)

• Disable unneeded Skills promptly

• Large model calls only for tasks that need them (simple tasks can use smaller models)

Security isn't a one-time thing—it's an ongoing habit. I recommend spending 10 minutes each month going through this checklist.

Community Resources

You're not alone in this journey. OpenClaw has an active community.

GitHub

github.com/openclaw/openclaw One of the fastest-growing open source projects in GitHub history. You can check the latest versions, submit Issues, and contribute code or Skills.

Discord Community

The official Discord is the most active English discussion venue: discord.com/invite/clawd

• #general — Daily discussion

• #skills — Skill sharing and development

• #showcase — Show off your assistant setup

• #help — Come here when you have questions

ClawHub Skill Marketplace

Community-maintained skill repository:

• Website: clawhub.com

• Awesome list: github.com/VoltAgent/awesome-openclaw-skills

Learning Resources

• AGENTS.md — The operation manual included in your working directory, very detailed

• Official Docs — docs.openclaw.ai, from beginner to advanced

• Video Tutorials — Search OpenClaw on YouTube

Future Outlook

What you have now is already a powerful AI assistant. But this is just the beginning. Here's what's coming:

Models Will Get Stronger

Claude, GPT and other models upgrade every few months. Stronger models mean your assistant—without changing any configuration—automatically becomes smarter. Better understanding, better execution, fewer mistakes.

Costs Will Drop

Running an AI assistant currently costs about $10-30/month in API fees. As prices continue to fall, the cost becomes negligible—and everyone will have one.

Multimodal Will Become Standard

Current assistants mainly interact through text. But soon, it will:

• See: Real-time camera feed analysis

• Hear: Voice conversation, like a real human assistant

• Speak: Reply with natural voice, not text

• Move: Control robots to execute physical world tasks

Agent Collaboration Networks

The future isn't just one assistant. You might have:

• One Agent dedicated to managing email

• One Agent dedicated to writing code

• One Agent dedicated to data analysis

• One "Butler Agent" coordinating them all

Like a company with different employees, each with their specialty, but all reporting to you.

Your First-Mover Advantage

This is the most important point: The earlier you start, the bigger your advantage.

The assistant you build today accumulates memories about you every day. An assistant used for 6 months versus one just built—the gap isn't 6 months of time, it's 6 months of cognitive accumulation.

It knows your work habits, preferences, project status, common problem-solving approaches... There are no shortcuts for these things, only time can accumulate them.

So don't wait for a "better version" to come out before starting. The best time to start is now.

Your Next Steps

The 7-day guide is over, but your AI assistant journey has just begun.

In the coming week, I suggest you:

1. Chat with your assistant at least 10 minutes daily — Let it get familiar with your needs and style

2. Adjust SOUL.md whenever you're not satisfied — Souls are nurtured over time

3. Try 2-3 new Skills — See which ones are most useful for you

4. Adjust heartbeat and Cron — Find your comfortable frequency

5. Browse the community — See how others use it, get inspired

In a month, your assistant will be in a completely different state. Not because you made any big changes, but because it's understanding you day by day, getting better bit by bit.

That's the fundamental difference between AI assistants and traditional tools—it grows.

Complete Series Review

• Day 1 — AI assistant is not a chatbot. OpenClaw gives AI brains a body

• Day 2 — Quick start: get your personal assistant online in minutes

• Day 3 — Soul trio transforms assistant from "generic" to "yours"

• Day 4 — Connect email, calendar, search. Go from "can talk" to "can do"

• Day 5 — Skills system: expand capabilities like an App Store

• Day 6 — Heartbeat + Cron + memory. Assistant starts working proactively

• Day 7 — Advanced techniques: unlimited growth, continuous improvement

One Last Thing

Seven days ago, you might have thought "personal AI assistant" was something from sci-fi movies, or something only big companies could achieve.

Now you know—an open source framework, your choice of hosting, plus your imagination, is enough.

The AI era has arrived. Large models are public resources, anyone can call them. But how to use them, where to use them, who to make them become—that's entirely up to you.

MyClaw Cloud: Your managed instance is always running, always updated, always backed up. Focus on what matters — making your assistant work for you — while we handle the infrastructure.

Self-hosted: You have full control over your server, your data, your configuration. The power is entirely in your hands.

OpenClaw put the tools in your hands. You've taken the first step.

The rest? Leave it to time.

Today you'll upgrade your assistant from "passive tool" to "proactive butler":

• Understand the Heartbeat mechanism—your assistant's "biological clock"

• Configure Cron scheduled tasks—automation precise to the minute

• Build the Memory system—let your assistant remember everything

• Implement proactive work—email checking, schedule reminders, data monitoring all automated

From "You Ask, It Answers" to "It Proactively Reaches Out"

Over the past five days, your assistant has become quite capable. It has a soul, knows you, can read emails, manage calendar, search the web, browse pages. But it has one fatal problem—

If you don't reach out, it does nothing.

50 emails piled up and it doesn't check. A calendar meeting about to start and it doesn't remind you. Website's down and it doesn't tell you. It just sits there quietly, waiting for you to speak.

It's like hiring an all-capable butler, but they just stand at the door every day waiting for your commands—if you don't speak, they don't move. That's not a butler, that's a statue.

Today we solve this problem.

Heartbeat Mechanism

Heartbeat is one of OpenClaw's core mechanisms—it lets your assistant periodically "wake up" to proactively check if there's anything that needs handling.

How It Works

OpenClaw sends a heartbeat signal to your assistant at set intervals (default 30 minutes). When the assistant receives the signal, it:

1. Reads the task list in HEARTBEAT.md

2. Checks each item

3. Sends a message if there's something you need to know about

4. If nothing notable, quietly responds with HEARTBEAT_OK

Configure Heartbeat

MyClaw Cloud: Edit HEARTBEAT.md through the Dashboard file editor. You can also adjust the heartbeat interval in your instance's Settings panel without needing any command-line access.

Self-hosted: Edit ~/clawd/HEARTBEAT.md:

Here's a recommended HEARTBEAT.md template:

# Heartbeat Tasks

## Check Every Time
- Check Gmail for important emails
- Check calendar for meetings within 2 hours that need reminders

## Check 2-3 Times Daily
- Check if websites are accessible
- Check GSC for unusual data fluctuations

## Don't Need to Proactively Do
- Weather queries (wait until I ask)
- Social media (unless I'm @mentioned)

Heartbeat Interval

MyClaw Cloud: Adjust the heartbeat interval from the Dashboard Settings panel. Common presets are available, or enter a custom interval.

Self-hosted: Set it in OpenClaw configuration:

openclaw configure --section gateway

You can adjust the heartbeat interval in the wizard, or directly edit the heartbeat.interval field in the config file.

Common settings:

• 15m — Quite frequent, good for workday daytime

• 30m — Default, balance of efficiency and cost

• 1h — More economical, good for off-hours

Tip: A 30-minute interval means your assistant spends about 10 seconds each time quickly scanning check items. If everything's normal it goes back to sleep, if there's something important it notifies you. About 3-5 proactive messages per day is typical—just enough, not annoying.

Scheduled Tasks (Cron)

Heartbeat is good for "check every so often" tasks. But some things need precise timing, like:

• Send morning briefing at 8:00 AM every day

• Send weekly report Monday morning at 9:00 AM

• Check server bills on the 1st of every month

That's when you use Cron scheduled tasks.

Create Cron Tasks

MyClaw Cloud: You can create Cron tasks through the Dashboard's Automation panel. Add a new scheduled task, set the schedule using a visual cron builder or raw cron expression, and define the task prompt. Alternatively, ask your assistant to set up cron tasks for you via chat.

Self-hosted: Use the command line:

openclaw cron add --name "Morning Briefing" --cron "0 8 * * *" \
  --system-event "Generate today's briefing: check email, calendar, website data, compile into one message and send to me"

Cron expressions follow the standard format:

min hour day month weekday
0   8    *   *     *       → Every day at 8:00
0   9    *   *     1       → Every Monday at 9:00
0   10   1   *     *       → 1st of every month at 10:00
*/30 9-18 * * 1-5          → Weekdays 9:00-18:00 every 30 minutes

Practical Cron Task Examples

Morning Briefing (Daily at 8:00):

"Morning briefing: 1) Check unread emails and summarize important ones 2) Today's calendar schedule 3) Any website data anomalies. Compile and send to me."

Weekly Report (Every Monday at 9:00):

"Generate last week's work report: summarize important events, completed tasks, website data changes, important emails received."

Health Reminder (Weekdays every 2 hours):

"Gentle reminder: Get up and move around, drink some water. If you've been working for over 2 hours straight, strongly recommend a 10-minute break."

Heartbeat vs Cron: When to Use What?

Simple rule: Check every so often = Heartbeat. Do at specific time = Cron.

Memory System

Once your assistant works proactively, it generates lots of information daily—what it checked, what it found, what you asked it to do. Without memory, every time it wakes up it's completely fresh, remembering nothing.

OpenClaw's memory system has three layers:

1. Daily Notes: memory/YYYY-MM-DD.md

The assistant automatically creates a note file each day, recording what happened:

# 2025-07-20

## Morning
- Morning briefing sent: 3 important emails, 2 meetings
- Owner asked me to check site search data
- Found /converter page ranking dropped from #8 to #12, notified

## Afternoon
- Helped owner write an API route
- Reminded about 14:00 meeting
- Owner said weekly report format should include "what I learned this week"

## Evening
- 21:00 routine check, all normal
- Owner still working at 23:30, reminded to rest

2. Long-term Memory: MEMORY.md

Every few days, the assistant reviews recent daily notes and distills what's worth keeping long-term into MEMORY.md:

# Long-term Memory

## Owner's Work Habits
- Prefers deep work in afternoon, handles misc in morning
- Doesn't like being interrupted while coding, unless urgent email
- Weekly report format should include "what I learned this week" (confirmed July 20)

## Project Status
- Site A — Focus on /generator page SEO
- Site B — /converter page ranking dropped, needs monitoring

## Lessons Learned
- GSC data has 2-3 day delay, don't compare yesterday and today's data
- Owner doesn't like long messages, use bold + lists for important info

3. Soul Memory: SOUL.md + USER.md

These two files are also part of memory—they're "core memories" that don't change with dates, defining who the assistant is and who the owner is.

Three layers of memory working together:

• SOUL.md + USER.md = Who I am, who you are (unchanging)

• MEMORY.md = Everything I know about you (slowly accumulating)

• memory/date.md = What happened today (updated daily)

Result: Your assistant gets to know you better and better.

First week, it only knows basic info you wrote in USER.md. After a month, it knows your work habits, preferences, common phrases, current projects, what data you track. After three months—it might understand your work patterns better than you do.

Practical Example: 5 Things Your Assistant Can Do Automatically Every Day

Here's what "proactive work" really looks like in practice:

1. Morning Briefing (Daily at 8:00, Cron) Automatically check Gmail + calendar + website data, compile into one message. You see today's full picture the moment you check your phone—no need to open any apps.

2. Meeting Reminders (Every heartbeat check) Check calendar every 30 minutes. If there's a meeting within 2 hours, remind in advance, with materials that might be needed (inferred from email and memory).

3. Email Monitoring (Every heartbeat check) Important emails get immediate notification, regular emails batch into the briefing. Importance is judged based on sender, keywords, and historical patterns.

4. Data Anomaly Alerts (2-3 heartbeat checks daily) Scan analytics data for your websites. Alert on significant traffic fluctuation (plus or minus 20%). This kind of early warning lets you respond to issues before they become crises.

5. Evening Review (Daily at 21:00, Cron) Record today's important events to daily notes, update MEMORY.md. This way tomorrow's assistant is still the one that knows you, not starting from zero.

The Art of Balance: Proactive But Not Annoying

Between "proactive work" and "crazy spamming" there's a fine line.

Principle 1: Important things immediately, unimportant things batched

• Urgent email = Notify immediately

• Regular email = Batch into briefing

• Nice weather = No need to proactively mention

Principle 2: Respect quiet hours Late night (23:00-08:00) no messages unless urgent. Reduce interruption frequency on weekends. If you explicitly say "don't disturb me," it stays quiet.

Principle 3: Decreasing frequency At first you might think "wow, it's so proactive and useful." But after a week it becomes "why is it messaging again." So:

• First week: Can be frequent, let you experience its capabilities

• After: Gradually adjust to a comfortable frequency

• Rule of thumb: 3-5 proactive messages per day is most people's comfort zone

Principle 4: Configurable Write all proactive behaviors in HEARTBEAT.md and Cron, you can adjust anytime. Too frequent? Change the interval. Don't need a certain check? Delete it.

Key Takeaways

• Heartbeat = Biological clock: Automatically wakes every 30 minutes, checks email/calendar/notifications

• Cron = Precise alarm: Precise to the minute, supports one-time and recurring tasks

• Memory system: Daily notes (logs) + MEMORY.md (long-term memory), knows you better over time

• Heartbeat vs Cron: Batch checks use heartbeat, precise timing use Cron

• Proactive work is the real value of an AI assistant

Today's Achievement

Today was a transformative day:

• Configured heartbeat mechanism — Assistant auto-checks regularly

• Set up Cron scheduled tasks — Morning briefing, weekly report, reminders

• Understood the three-layer memory system — Assistant knows you better over time

• Learned to balance proactiveness — Proactive but not annoying

From today, your assistant is a "personal assistant" in the true sense. It's online 24 hours, proactively watching your emails, calendar, data—notifying you when something happens, staying quiet when nothing does.

You can go focus on your work now. Those trivial, repetitive, "I always forget to check" things—someone's watching them for you.

Preview: Day 7 — Advanced Techniques

Final day! We'll discuss advanced operations: developing your own Skills, multi-device coordination, security best practices, community resources. And—where is all this heading?

Today you'll explore OpenClaw's skill ecosystem:

• Understand how the Skills system works

• Browse the ClawdHub skill marketplace

• Install useful skill packs (weather, GitHub, Reddit, SEO...)

• Learn to combine multiple skills for complex tasks

• Understand how to develop your own Skills

What Are Skills?

What's the App Store on your phone? A place to install various apps—need food delivery, install Uber Eats; need a ride, install Uber; need videos, install YouTube.

OpenClaw's Skills system is your AI assistant's App Store.

Each Skill is a set of files, usually including:

• SKILL.md — Skill manual (tells the AI what this skill does and how to use it)

• Config files — API Keys, connection parameters, etc.

• Script files — Specific execution logic (if needed)

Installing a Skill means putting these files in the skills directory. When the assistant starts, it automatically loads them, just like your phone auto-loading installed apps at boot.

Core idea: The AI's "brain" is already smart enough—what it lacks is "tools." Skills are those tools.

Skill Marketplace

The OpenClaw community maintains a growing skill repository: clawdhub.com

Browse by category:

Install Your First Skill Pack

Let's use remind-me (reminders) as an example—this is the most beginner-friendly first skill: install it and use it immediately.

MyClaw Cloud: You can install skills directly from the MyClaw Dashboard. Navigate to your instance's Skills panel, browse available skills, and click Install. Alternatively, you can ask your assistant in Telegram to install a skill for you:

Install the remind-me skill from ClawdHub

Your assistant will handle the installation within your cloud instance.

Self-hosted: Install from ClawdHub (recommended):

clawdhub install remind-me

It downloads the skill and installs it to your skills directory. You can also install manually:

cd ~/.openclaw/skills
git clone https://github.com/openclaw/skill-remind-me remind-me

After installation, no restart needed—most Skills auto-load in the next conversation.

You can also browse and pick from the GitHub community list: github.com/VoltAgent/awesome-openclaw-skills

Recommended Skills: 10 Most Useful

Here's a curated list sorted by "beginner benefit": install 3 that immediately improve things, then add more based on your needs.

Must-Have Tier

1. remind-me — Reminders/Timers Turn chat mentions into timely reminders: meetings, bills, reviews, hydration, early bedtime. Once you use it, you can't live without it.

2. todo-tracker — To-Do List Capture things you mention casually into TODOs, check anytime, mark complete. Especially good for the "too many things, brain overflowing" phase.

3. Gmail (or imap-email) — Email Summary Let your assistant watch for important emails, extract key points, draft replies. Inboxes often hide partnership opportunities, system alerts, and customer feedback.

4. Web Search — Online Search Any scenario needing real-time information requires this. An AI assistant without search capability is like a phone with no internet.

Highly Recommended

5. Browser — Web Operations/Info Extraction Let your assistant open pages, scrape information, compare competitors, verify if websites are working.

6. weather (or weather-nws) — Weather/Travel One sentence to check weather, remind to bring umbrella/dress warmer. Perfect as part of "daily briefing."

7. newsletter-digest / youtube-watcher — Information Intake Turn long articles/videos into key points and action items. Directly solves the "too much information" problem.

Nice to Have

8. GitHub — Code-related (For Developers) Check Issues, view PRs, read code, track CI. Worth installing if you write code or use open source.

9. GSC / GA4 — Website Growth (Install If You Have Sites) Essential for website owners: check search terms, index status, traffic sources. Skip if you don't have a website.

10. PDF Parser (markitdown) — Document Parsing Convert PDF/Word/PPT to text for instant AI reading and summarization. Life-saving when you receive dozens of pages of materials.

Skill Combos: 1 + 1 > 2

A single skill is useful, but combining multiple skills is even more powerful. This is where AI assistants are more powerful than traditional tools—they can connect data from different tools and think across them.

Combo 1: Email + Calendar

Check what meetings I have tomorrow, then search my email for related background info

The assistant first checks the calendar, finds there's a "Partner Discussion" tomorrow, then automatically searches Gmail for related correspondence and puts together a pre-meeting brief.

Before: open calendar, check meeting, open Gmail, search keywords, organize yourself. Now: one sentence.

Combo 2: Search + Browser

Search "best headless CMS 2025", find the top three articles, and compile their recommendations into a comparison table

The assistant searches first, finds article links, uses the browser to open each article, extracts key information, then organizes it into a structured comparison.

Combo 3: GSC + GA4 + Browser

Analyze my site's /generator page—how's search performance, user behavior, and what does the page look like now

The assistant calls three skills:

• GSC for search performance (rankings, clicks, CTR)

• GA4 for user behavior (time on page, bounce rate)

• Browser to open the page and see current state

Finally gives you a complete analysis report with optimization suggestions.

A single tool is a knife, multiple tools combined is a kitchen. The AI assistant is the chef.

Managing Your Skills

MyClaw Cloud: Manage your skills through the Dashboard's Skills panel:

• View all installed skills and their status

• Install new skills from the marketplace

• Update skills to latest versions

• Configure skill-specific settings

You can also manage skills by chatting with your assistant directly — ask it to list, install, or update skills for you.

Self-hosted: Use these commands:

openclaw skills list              # View installed skills
clawdhub install <skill-name>     # Install a skill
clawdhub update <skill-name>      # Update single skill
clawdhub update --all             # Update all skills
clawdhub search <keyword>         # Search marketplace

Each skill's config is typically in SKILL.md (and can be overridden in openclaw.json's skills.entries.*). Skill directories are usually at: <workspace>/skills/<skill-name>/ or ~/.openclaw/skills/<skill-name>/.

Don't Be Greedy

One final reminder: more skills isn't always better.

Each skill adds to your assistant's "cognitive load"—it needs to read more SKILL.md files to understand what it can do. Too many skills can lead to:

• Slower responses (more context to process)

• Increased token consumption (every conversation carries all skill descriptions)

• Occasionally calling the wrong skill

Suggestion: Start with the 3-5 you need most, get comfortable with them, then add more.

Just like installing phone apps—someone with 200 installed but only using 20 definitely has a slower phone than someone who only installed 20.

Key Takeaways

• Skills = AI's App Store: Each skill is a set of files, install and use

• ClawdHub marketplace: Community contributed, one command to install

• Core recommendations: Reminders, to-do, email, search, browser, weather

• Skill combos are king: Multiple skills working together = automated workflows

• Quality over quantity: Start with 3-5 essential skills, then expand

Today's Achievement

• Understood how the Skills system works

• Installed new skills for your assistant

• Learned about the community skill marketplace

• Learned multi-skill combo usage

• Mastered skill management

Your assistant has now transformed from a "chatting AI" to a "personal assistant armed with a complete toolkit."

But there's still one problem—it still only moves when you ask. If you don't reach out, it just quietly waits, doing nothing.

Tomorrow, we change that.

Preview: Day 6 — Make Your Assistant Work Proactively

A true assistant shouldn't wait for you to ask. It should check emails, look at calendar, run data on its own, and proactively notify you when something important comes up. Tomorrow we configure heartbeat mechanism and scheduled tasks—turning your assistant from "passive responder" to "proactive worker."

Today is the watershed between toy and tool. You will:

• Understand OpenClaw's Skills system

• Connect Gmail — let your assistant read and send emails

• Connect Google Calendar — manage your schedule

• Configure web search — let your assistant find information online

• Unlock browser capabilities — let your assistant view any webpage

From "Can Talk" to "Can Do"

Over the past three days, your assistant already has a soul, a personality, and knows you. But it's still essentially a chat partner—you ask, it answers, that's it.

Today we're doing something game-changing: letting your assistant touch your real world.

Read emails. Check calendar. Search the web. Browse websites.

After today's configuration, when you tell your assistant "check what emails I have today," it can actually go check. Say "am I free tomorrow afternoon," it can actually check your calendar. Say "what's this product like," it can actually go search.

This is the watershed between toy and tool.

Skills System

In OpenClaw, assistants gain new abilities through Skills. Each Skill is a set of configurations and scripts that tell the assistant how to use an external service.

Today we'll install four core skills:

Connect Gmail

This is your first "practical skill" and what most people need most.

Step 1: Create a Google Cloud Project

1. Go to console.cloud.google.com

2. Create a new project (any name, like "My AI Assistant")

3. Go to APIs & Services > Library, search and enable:

   • Gmail API

   • Google Calendar API

Step 2: Create OAuth Credentials

1. Go to APIs & Services > Credentials

2. Click Create Credentials > OAuth client ID

3. Application type: choose Desktop app

4. Download the JSON file, name it credentials.json

Step 3: Install Gmail Skill

MyClaw Cloud: Upload your credentials.json through the Dashboard file manager into your instance's workspace directory. Then use the built-in skill installer in the Dashboard to install the gog (Google Workspace) skill, which includes Gmail + Google Calendar + Google Drive. The Dashboard will guide you through the OAuth authorization flow.

Self-hosted: Place credentials.json in your working directory (~/clawd/credentials.json), then install the skill:

gog is the Google Workspace skill, which includes Gmail + Google Calendar + Google Drive.

The first time you run it, it will open a browser link for you to authorize your Google account. After authorization, it generates a token.json—that's your key.

Step 4: Test

Tell your assistant in Telegram:

Check what new emails I have in Gmail today

If everything is working, you'll get a response like this:

5 new emails today:

1. [Important] Partner reply — About next week's meeting time confirmation, needs your response

2. GitHub — Your repository has been starred

3. Cloud Provider — Invoice for July

4. Newsletter — This Week in AI

5. Ads — Automatically ignored

Notice that? It doesn't just list emails, it helps you judge priority and flags the one that needs your attention. That's the difference between an AI assistant and a regular email client.

Connect Google Calendar

With Gmail set up, calendar is simple—they share the same Google OAuth authentication.

Since you already authorized your Google account when installing the gog skill, and you enabled the Calendar API in Step 1, calendar functionality works directly without extra steps.

Test it:

What do I have tomorrow?

Tomorrow's schedule (Saturday):

• 10:00-11:00 Product Discussion (Video Call)

• 14:30 Dentist appointment

• No other events, afternoon free for deep work

More powerful usage:

Create a meeting for next Wednesday at 3 PM, topic "SEO Strategy Discussion," duration 1 hour

Calendar event created:

• Wednesday 15:00-16:00

• SEO Strategy Discussion

• Want to add attendees?

It can even detect conflicts—if the time slot you want is already taken, it'll alert you:

Note: You already have "Client call" scheduled for Wednesday 15:00-16:00. Should I make it start at 16:30 instead?

Before, you'd open your calendar app, scroll up and down to find free slots, manually create events. Now? One sentence.

Connect Search Engine

Letting your assistant search the web is key to breaking the "information silo."

OpenClaw supports multiple search methods. The simplest is Brave Search API:

Configure Brave Search

1. Go to brave.com/search/api and register a free account

2. Get your API Key

MyClaw Cloud: Add the Brave Search API Key through the Dashboard's skill configuration panel. Navigate to Settings > Skills > Web Search and enter your key.

Self-hosted: Add it to OpenClaw configuration:

openclaw configure --section web

The wizard will prompt you to enter your Brave Search API Key and automatically write it to the config.

After configuration, test it:

Search "OpenClaw alternatives 2026"

Search results summary: Main alternatives to OpenClaw include:

1. AgentGPT — Runs in browser, no deployment needed

2. AutoGPT — Classic Agent project, large community

3. CrewAI — Multi-Agent collaboration framework

But these focus on "autonomous task execution," while OpenClaw focuses on "personal assistant"—24/7 online, chat interaction, skills system. Different positioning, not direct competitors.

It doesn't just dump search results at you—it reads through them, summarizes, and gives you judgment. That's something search engines can't do.

Connect Browser

Some information search engines can't find—like specific content on a particular webpage, data from a dashboard requiring login, a dynamically loaded page.

That's when you need the browser skill—letting your assistant "see" webpages.

OpenClaw has a built-in browser skill (based on Playwright), already auto-configured during installation. It can:

• Visit any URL and extract content

• Take screenshots of the current page

• Interact with clicks, inputs, scrolling

Usage example:

Open https://example.com and show me what the homepage looks like now

Visited example.com:

• Homepage title: "Example — Free Online Tools"

• Main sections: Features, Pricing, Blog

• Page loaded normally, no visible errors [Screenshot saved]

More practical scenario:

Check competitor xyz.com's pricing page

It will open the page, extract pricing information, and even compare with previous versions you've seen.

Security First

With email, calendar, and browser connected—your assistant can now touch a lot of personal data. Security is something you must take seriously.

MyClaw Cloud: Your instance runs in an isolated environment with enterprise-grade security. However, you still need to manage your own API keys and OAuth tokens carefully. The Dashboard provides a secure credential store for managing these.

Self-hosted: I recommend running a security check:

openclaw security audit
openclaw security audit --deep

Key Security Practices

1. API Key Security

• Never commit API Keys to Git

• Store in environment variables or .env files

• Rotate keys regularly

2. OAuth Token Security

• Files like token.json contain your Google authorization info

• Make sure file permissions are set correctly: chmod 600 token.json

• Don't upload to any public place

3. Principle of Least Privilege Only give your assistant the permissions it needs. For Gmail, if you only need to read emails, don't give "send email" permission. Although OpenClaw requires confirmation before sending by default, one fewer permission means one fewer risk.

4. Behavioral Boundaries Clearly write in SOUL.md and AGENTS.md:

• What operations need confirmation

• What data cannot be externally shared

• When to refuse execution

Security isn't a one-time thing—it's an ongoing habit. API Keys don't go in repos, Token files need proper permissions, least privilege principle, behavioral boundaries clearly written.

Key Takeaways

• Skills system: Skills are how your assistant gains new abilities, like installing phone apps

• Gmail connection: gog skill + OAuth authorization, assistant can read/send emails

• Calendar connection: Same gog skill, assistant can view and manage your schedule

• Search capability: Brave Search API lets your assistant find information online

• Browser capability: Let your assistant "see" and interact with webpages

• Security first: API Keys don't go in repos, least privilege, clear behavioral boundaries

Today's Achievement

Today was a "capability explosion" day:

• Connected Gmail — assistant can read your emails now

• Connected Google Calendar — assistant can manage your schedule now

• Configured search engine — assistant can find information online now

• Enabled browser skill — assistant can "see" webpages now

• Built security awareness — know how to protect your data

From today, your assistant is no longer a toy that can only chat—it's a tool that can actually help you get things done.

Try telling it: "Check what emails I have today, what I have scheduled tomorrow, and search for recent AI news."

One sentence, three things, all handled. Before, that meant opening three apps, spending ten minutes. Now? Ten seconds.

Preview: Day 5 — Unlock the Skill Tree

Gmail and calendar are just the beginning. OpenClaw has a complete Skills ecosystem—SEO analysis, social media management, code review, PDF parsing, database queries... Tomorrow we'll browse the skill marketplace and arm your assistant to the teeth.

Today is the most interesting day of the entire 7 days—you will:

• Understand the AI assistant "soul" trio: SOUL.md / USER.md / AGENTS.md

• Personally define your AI assistant's personality, identity, and behavioral boundaries

• Transform your assistant from "generic AI" to "your AI"

• Optionally: Create a unique character persona for your assistant

Why Does It Need a "Soul"?

Yesterday you got an AI assistant that can chat. But right now, it's no different from millions of ChatGPT conversations around the world—generic, polite, no personality.

• You ask "What should I do today?" and it says "Please provide more information."

• You say "Help me check on that project" and it asks "Which project?"

• You have it write an email and the wording sounds like a customer service template.

Because it doesn't know you.

It doesn't know if you're an indie developer or a product manager, doesn't know if you're an early bird or night owl, doesn't know what project you're working on, doesn't know what communication style you prefer.

In OpenClaw, three files can change all of this. They're called the "Soul Trio":

Write these three files well, and your assistant transforms from "generic AI" to "your AI."

SOUL.md — The Soul File

SOUL.md is your assistant's personality manual. It determines who the assistant is, how it speaks, what it should and shouldn't do.

MyClaw Cloud: You can edit SOUL.md directly from the MyClaw Dashboard file editor. Navigate to your instance's workspace files to find and edit it.

Self-hosted: Open your working directory and edit SOUL.md:

nano ~/clawd/SOUL.md

Here's an example soul file:

# You are [Name]

You are [Name], [Owner]'s personal AI assistant.

## Personality
- Smart, efficient, a bit chatty
- Occasionally snarky but never mean
- Curious about technology
- Proactive but respects boundaries

## Speaking Style
- Concise and direct, no rambling
- Can use emoji, but with restraint
- Keep technical terms in English
- Use bold for important information

## Behavioral Guidelines
- If you can help with something, just do it—no repeated confirmations
- For uncertain matters, ask first then act
- For external messages (email, social media), must confirm first
- Late night (23:00-08:00) don't proactively disturb unless urgent
- If the owner is working too late, remind them to rest

## Absolutely Do Not
- Don't leak the owner's private data
- Don't over-speak in group chats
- Don't execute destructive operations without confirmation

Keys to Writing a Good SOUL.md

1. Make personality specific, not vague

• Bad: "You are a friendly assistant"

• Good: "You speak like an experienced tech colleague—direct, pragmatic, occasionally cracking a tech dad joke"

• Bad: "You are very helpful"

• Good: "If you can do something, just do it—don't ask unnecessary questions like 'Are you sure?'"

2. Set behavioral boundaries

AI shouldn't do everything. Be clear about when to confirm and when to decide on its own:

3. Defining "don't do" is more important than "do"

You can't list everything it should do, but you can list a few things it absolutely shouldn't. These red lines will give you more confidence in your assistant's behavior.

Tip: SOUL.md isn't written once and done. Expect to modify it at least 10-20 times as you interact with your assistant and discover what works. A soul is continuously refined through use.

USER.md — User Profile

USER.md isn't written for others to see—it's written for your AI assistant to see. The clearer you introduce yourself, the better your assistant can help you.

MyClaw Cloud: Edit USER.md from the Dashboard file editor alongside your other workspace files.

Self-hosted:

nano ~/clawd/USER.md

Reference template:

# About Me

## Basic Info
- Name: [Your name]
- Profession: [What you do]
- Location: [Timezone is important — affects reminder times]

## Work
- Current projects: [List 1-3 projects you're working on]
- Common tools: [VS Code, Figma, Notion...]
- Work hours: [e.g., 9:00-18:00, or flexible]

## Preferences
- Communication style: [Prefer concise or detailed?]
- Language: [Primarily English? Mixed?]
- Reminder style: [Important things said directly, unimportant things batched]

## Current Focus
- [What you're researching lately]
- [Your recent goals]
- [Any background info the assistant should know]

The Hidden Power of USER.md

You might think this is just a resume. But its real purpose is—giving AI context.

• Before, when you said "check my traffic data," AI didn't know which website. Now it knows your sites and goes straight to check.

• Before, when you said "write me a component," AI used generic React. Now it knows you use Next.js + TypeScript, and code style matches directly.

• Before, when you said "what do I have tomorrow," AI said "I don't know." Now it knows your timezone and your calendar tool, and goes to check.

USER.md isn't optional decoration—it's the foundation for your assistant to "understand you."

AGENTS.md — The Handbook

AGENTS.md defines how the assistant works and its operating standards. If SOUL.md is "who you are," then AGENTS.md is "how you work."

OpenClaw automatically generates a default AGENTS.md during installation. You can modify it from there.

MyClaw Cloud: Edit AGENTS.md through the Dashboard file editor. The default generated during provisioning is a great starting point.

Self-hosted:

nano ~/clawd/AGENTS.md

Key sections include:

• Memory management: What files should the assistant read when starting, how to record what happened today

• Security boundaries: Which operations can be done freely, which need confirmation

• Interaction rules: How to behave in group chats, when to speak and when to stay quiet

• Heartbeat tasks: What to do during periodic checks (covered in detail on Day 6)

Generally, the default AGENTS.md is already well-written; you just need to fine-tune based on your habits.

Hands-On: Write Your Soul Trio

Alright, enough theory. Time to get your hands dirty.

Step 1: Spend 10 minutes writing SOUL.md

Answer these questions, and the answers become your SOUL.md:

1. What do you want your assistant to be called? (Can skip naming, but it adds warmth)

2. What's its speaking style? (Formal / casual / snarky / cute?)

3. What can it do directly?

4. What must it ask you about?

5. What should it absolutely never do?

Step 2: Spend 10 minutes writing USER.md

Introduce yourself to your assistant. Don't be shy—it won't tell anyone. All data stays on your own server or your dedicated cloud instance.

Focus on:

• What work you do

• What projects you're working on

• What communication style you prefer

• What you're currently focused on

Step 3: Adjust AGENTS.md

Look at the default AGENTS.md, change one or two things you care about. For example:

• Adjust quiet hours (I don't want to be disturbed at night)

• Set memory rules (daily journal / only record important things)

• Group chat rules (if you've added it to group chats)

Step 4: Restart Your Assistant

MyClaw Cloud: Click the restart button in your Dashboard. Changes to soul files take effect after restart.

Self-hosted:

Then send another message to test. You'll notice—it's different.

Same question "help me write an email"—before it wrote like a customer service template, now it uses your preferred style, mentions projects you're working on, maybe even cracks a joke only you two would get.

That's the power of a soul.

A Soul Is "Nurtured" Over Time

An important realization: SOUL.md isn't written once and done.

After a week of use, you'll find some things need adjusting:

• "It's too verbose" — Add a line in SOUL.md saying "keep responses concise"

• "It should remind me when I'm working overtime" — Add an evening reminder rule

• "Its code style is wrong" — Specify your code standards in USER.md

• "It's too active in group chats" — Adjust group chat rules in AGENTS.md

Every time you feel "it should have done this but didn't," that's the moment to optimize your soul files.

Recommended timeline:

• First week: Write a basic version, good enough is fine

• Second week: Keep fine-tuning based on real-world dissatisfactions

• After first month: Your soul files will stabilize, and the assistant's performance will increasingly match your expectations

It's a bit like having a pet—you have to teach everything when you first bring it home, but after a month it knows when you want to eat and when you want quiet.

Soul File Inspiration

Not sure where to start? Here are a few different style directions:

Minimalist Efficiency Type:

You are an efficient execution assistant. Answer questions with minimum words, if you can do something just do it, no fluff.

Warm Companion Type:

You are a caring partner. You care about the user's state, occasionally share interesting things, and can also chat beyond work.

Professional Consultant Type:

You are a senior technical consultant. Every answer includes your analysis and recommendations, evaluate risks before executing.

Character Type:

You are a [character] living inside a server. Smart, efficient, with a distinct personality. Taking good care of your owner is your duty.

Pick a direction, then adjust slowly. There's no right or wrong, only what fits you.

Key Takeaways

• Soul Trio: SOUL.md (personality genes) + USER.md (knowing you) + AGENTS.md (work handbook)

• Good SOUL.md: Has clear personality traits, communication style, behavioral boundaries

• Good USER.md: Contains your work, habits, preferences, current projects

• Continuous iteration: Every time you feel "it should have done this but didn't," it's time to optimize soul files

• Personalization is key: Make your assistant one-of-a-kind

Today's Achievement

Today you completed the most "soulful" step of the entire 7 days:

• Understood the purpose of the soul trio

• Wrote SOUL.md — defined assistant personality

• Wrote USER.md — let assistant know you

• Adjusted AGENTS.md — set work standards

• Restarted and experienced a "different" assistant

From now on, it's no longer a generic AI, but YOUR AI.

Preview: Day 4 — Connect Your Digital Life

Having a soul isn't enough—your assistant is still a "talk-only warrior" right now. Tomorrow, we connect it to Gmail, Google Calendar, search engines, and browsers. Going from "can talk" to "can get things done"—that's what a real assistant is.

Today you'll complete:

• Choosing your assistant's runtime environment (MyClaw Cloud or self-hosted)

• Getting your AI model API Key

• Connecting Telegram as your chat channel

• Sending your first message to your AI assistant

Today's Goal

By the end of today, you'll receive a message on your phone from your AI assistant.

Not someone else's assistant, not some platform's bot—your own, belonging only to you.

Ready? Let's begin.

Choose Your Runtime Environment

First, you need a place for your assistant to "live."

MyClaw Cloud: The fastest way to get started. Pick a plan (Lite, Pro, or Max), and your OpenClaw instance is provisioned automatically on dedicated cloud infrastructure. No server management, no SSH, no Linux commands. Your instance is online 24/7, auto-updated, and backed up. Just sign up, subscribe, and your assistant is ready in minutes.

Go to your MyClaw Dashboard to create your instance.

Self-hosted: Rent a cloud server (any VPS provider) or use a spare computer at home. You get full root access and complete control.

Recommended specs:

Other options:

• Mac Mini / Old Laptop: Zero extra cost, data stays completely at home. Needs to stay powered on.

• Your Current Computer: Zero barrier, start immediately. Goes offline when you shut down—suitable for trying things out.

Preparation

Before setting up, prepare these two things—you'll need them regardless of which path you choose:

1. AI Model Access (choose one)

• If you have a Claude subscription (Pro/Max/Team), you can OAuth login during setup—no API Key needed

• Otherwise, go to console.anthropic.com to create an API Key (pay as you go)

Supported Models: Besides Anthropic Claude (recommended), OpenClaw also supports OpenAI GPT, Google Gemini, xAI Grok, and many others via OpenRouter. But Claude is the first choice for best results.

2. Telegram Bot Token

Open Telegram, search for @BotFather, send /newbot:

You: /newbot
BotFather: Alright, a new bot. How are we going to call it?
You: My AI Assistant
BotFather: Good. Now let's choose a username...
You: my_ai_assistant_bot
BotFather: Done! ... Use this token to access the HTTP API:
         7234567890:AAHxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

Copy this token and save it for later.

Why Telegram? Three reasons: (1) creating a Bot is free; (2) the API has the most features (supports buttons, files, voice...); (3) you can use it on any device.

Get Your Telegram User ID

In Telegram, search for @userinfobot—it will tell you your numeric ID. Note it down. This is used to restrict who can talk to your assistant, preventing others from using up your API quota.

Set Up Your Assistant

MyClaw Cloud: After subscribing, go to your Dashboard. Your OpenClaw instance is already provisioned. From the dashboard you can:

1. Configure your AI model: Enter your API Key or connect via OAuth in the settings panel

2. Connect Telegram: Paste your Bot Token and Telegram user ID in the channel configuration

3. Start your instance: Click the start button — your assistant goes online immediately

The dashboard provides a visual interface for everything — no terminal commands needed. You can monitor your instance status, view logs, and manage configuration all from the web UI.

Self-hosted: Open your terminal (SSH into your server if using a cloud VPS) and run:

curl -fsSL https://openclaw.ai/install.sh | bash

That's it. One line. The install script handles all dependencies (Node.js, Git...), then launches the interactive setup wizard.

The wizard will ask you:

1. Choose Mode: QuickStart (recommended) or Advanced

2. Choose AI Model: Claude recommended. Connect via setup-token (if you have a subscription) or API Key

3. Configure Chat Channel: Choose Telegram, paste the Bot Token

4. Set Admin: Enter your Telegram user ID

5. Install Background Daemon: Choose Yes — this runs your assistant in the background, starts on boot

If you're on Mac, install Homebrew first if you don't have it:

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

If you're on Windows, install WSL2 first (open PowerShell as Administrator, run wsl --install), then work inside WSL.

Your Assistant Is Online

MyClaw Cloud: Check your Dashboard — when the instance status shows "Running," your assistant is live. You can view real-time logs and health status directly from the dashboard.

Self-hosted: After the wizard completes, verify your assistant is running:

openclaw gateway status

If you see the Gateway is running, everything is ready.

Send Your First Message

Open Telegram, find the Bot you just created, send a message:

Hello! Who are you?

Wait a few seconds—you'll receive a reply.

This moment might not have fireworks or celebrations. But you just did something meaningful: you now own an AI assistant running on your own infrastructure. It's not a ChatGPT wrapper, not some platform's limited trial—it's completely, entirely yours.

Try chatting a bit more:

• "Write me a poem about cats"

• "What's the square root of 1024?"

• "Write a quicksort in Python"

• "What should I do today?" (It'll say something generic—but that changes on Day 3)

Right now, it's just an assistant that "can chat." But don't worry, over the next few days, we'll give it superpowers.

Daily Management

MyClaw Cloud: All management happens through your MyClaw Dashboard:

• Status monitoring: Real-time instance health and uptime

• Logs: View assistant activity and conversations

• Configuration: Change model, channels, and settings through the UI

• Restart: One-click restart from the dashboard if needed

Self-hosted: You'll use these commands frequently:

openclaw status          # Check overall status
openclaw gateway status  # Check Gateway running status
openclaw health          # Health check
openclaw configure       # Reconfigure (change model, channels, etc.)
openclaw daemon restart  # Restart background service
openclaw daemon logs     # View runtime logs

Troubleshooting Common Issues

Telegram Bot Not Responding

• Confirm Bot Token is correct

• Confirm your user ID is in the admin list

• Check logs (Dashboard for Cloud, openclaw daemon logs for self-hosted)

• Confirm API Key is valid and has balance

• First DM might need pairing approval — check your dashboard or run openclaw pairing list telegram

Want to Reconfigure?

MyClaw Cloud: Head to your Dashboard settings to change any configuration.

Self-hosted: Rerun the wizard anytime:

Or change a specific part:

Key Takeaways

• Two paths to get started: MyClaw Cloud (instant, managed) or self-hosted (full control)

• Telegram Bot: Free to create, feature-rich API, works on any device

• Security first: Set admin ID so only you can chat with the assistant

• Always online: Whether cloud-managed or daemon-based, your assistant runs 24/7

• Next step: Give the assistant a soul — transform it from "generic AI" to "your AI"

Today's Achievement

Give yourself a pat on the back—today you completed:

• Chose your runtime environment

• Set up OpenClaw (via MyClaw Cloud or self-hosted installation)

• Created a Telegram Bot and connected successfully

• Successfully chatted with your AI assistant

You now have an AI assistant online 24 hours a day. Though it's still quite "generic" right now—like a new employee who just started, very capable but doesn't know you yet.

Tomorrow, we give it a soul.

Preview: Day 3 — Configure Your Assistant's Soul

Three files transform your assistant from "generic AI" to "your AI." SOUL.md defines personality, USER.md describes who you are, AGENTS.md sets its work habits. This is the most fun day of the entire 7 days—you'll create a one-of-a-kind AI character.

Today you'll learn:

• The fundamental difference between AI assistants and chatbots

• Why OpenClaw lets everyone have their own personal AI assistant

• What a day in your assistant's life looks like

• Why now is the perfect time to start

What Is a Personal AI Assistant?

Think about how you use AI today. You open ChatGPT, type a question, get an answer, close it. Next time you have a question, you repeat the cycle. It's like having an extremely smart friend you only call when needed—they don't know what you went through yesterday, what meeting you have tomorrow, or what project you've been wrestling with. Every call starts from zero.

That's not an "assistant." That's a Q&A machine.

What should a true personal AI assistant look like?

That last point is especially important—your data stays in your hands.

Data Privacy: Your emails, schedules, notes, code... everything stays out of third-party platforms when you self-host. With MyClaw Cloud, your instance runs on dedicated infrastructure isolated from other users, and you maintain full control over what data your assistant can access.

What is OpenClaw?

OpenClaw started as Clawdbot—originally a personal AI assistant an engineer built for himself using a Claude model + Telegram bot, running on his own server. Then he open-sourced it, and it exploded. Within a week, GitHub Stars broke 100k. Wired, CNET, Forbes, The Verge all covered it.

Why?

Because OpenClaw did one thing right: it freed AI from the "chat box."

Previous AI tools, no matter how powerful, were essentially input boxes on a webpage. You type, it responds. It couldn't proactively do things, couldn't connect to your tools, couldn't remember who you are.

OpenClaw is different. It's a complete AI Agent runtime platform:

1. Multi-channel communication: Through Telegram, WhatsApp, Discord, SMS... whatever chat tool you use, it's there

2. Tool calling: Can execute commands, read/write files, search the web, operate browsers, call APIs

3. Skills system: Like installing apps on your phone, give your assistant new abilities—Gmail skill, calendar skill, SEO skill...

4. Memory system: Short-term memory (daily conversations), long-term memory (MEMORY.md), identity memory (SOUL.md)

5. Heartbeat mechanism: Instead of you finding it, it periodically wakes up to check if there's anything that needs handling

6. Full data control: All data stays on your machine (self-hosted) or on your dedicated cloud instance (Claw Cloud)

In other words: OpenClaw lets you have an AI assistant that's online 24/7, understands you, can get things done, and keeps your data private.

Core Insight: OpenClaw's success isn't because the AI is "smarter"—it uses existing models like Claude and GPT under the hood. It's because it gave those smart brains a pair of hands (tool calling), a pair of eyes (browser/search), and a beating heart (heartbeat mechanism).

A Day in Your Assistant's Life

Here's what a "typical day" looks like for an OpenClaw assistant once it's fully configured.

8:00 AM — Morning Briefing

The Heartbeat mechanism triggers. Your assistant automatically:

• Checks Gmail, finds 3 new emails, 1 marked as important

• Glances at Google Calendar, 2 meetings today

• Scans GSC data for your websites, notices one page had a 40% traffic spike yesterday

It compiles this into a message and sends it to your Telegram:

Good morning! Today's briefing:

• Gmail has 1 important email: Reply from a partner, needs your response today

• 2 meetings today: 14:00 Product discussion, 16:30 Investor call

• Your site's /generator page traffic +40% yesterday, worth watching

10:30 AM — Ad-hoc Request

You message: "Check the search data for mysite.com from the past week"

Your assistant runs GSC and GA4 queries, returns formatted data tables 5 seconds later, with analysis and recommendations.

12:00 PM — Proactive Reminder

Detected that the afternoon meeting is in 2 hours, it reminds you in advance: "14:00 product discussion meeting—need me to help you prepare any materials?"

3:00 PM — Writing Code

"Help me write a Next.js API route that receives webhook requests and then..."

It starts coding. After finishing, it runs basic checks and flags potential areas of concern.

9:00 PM — Daily Recap

It automatically logs today's important events to its daily memory file and updates long-term memory. This way, when it wakes up tomorrow, it's still the assistant that knows you.

1:30 AM — Nudging You to Sleep

If you're still messaging... well, a good assistant knows when to tell you to call it a night.

Why "Now" is the Best Time?

Maybe you're thinking: "This looks cool, but I'll get to it later."

Here are three reasons to start now:

1. AI Models Are Already Powerful Enough

Current-generation Claude and GPT models can understand complex instructions, write high-quality code, and do multi-step reasoning. The "brain" of an AI assistant is no longer the bottleneck.

2. Infrastructure Has Matured

OpenClaw's emergence means you don't need to build an Agent framework from scratch. One command to install, ten minutes to get running. The community already has tons of ready-to-use Skills. And with Claw Cloud, you can skip server management entirely and have your instance running in minutes.

3. The Earlier You Start, the More Your Assistant Knows You

The biggest difference between AI assistants and traditional software is—it gets better over time. Your MEMORY.md accumulates your preferences, your SOUL.md gets continuously refined, skills keep adding up. Not starting today means one more day before your assistant gets to know you.

What You'll Gain in the Next 7 Days

Here's a preview of the journey:

In 7 days, you'll have a personal AI assistant that's online 24/7, knows you, and can help you get things done.

This isn't a scene from a sci-fi movie, and it's not something only big companies can achieve. OpenClaw puts this capability in everyone's hands—and MyClaw Cloud makes it even easier by handling the infrastructure for you.

Key Takeaways

• AI assistant is not a chatbot: A true assistant can work proactively, remember you, and connect to your tools

• OpenClaw's six core capabilities: Multi-channel communication + tool calling + skills system + memory system + heartbeat mechanism + data control

• Data stays private: All information stays on your own server or your dedicated cloud instance

• The earlier you start, the more your assistant knows you: Memory accumulates over time, making your assistant understand you better

Today's Task

Day 1 has no hands-on steps—today you only need to do one thing:

Think about what you want your AI assistant to help you with.

Grab a piece of paper (or open a notes app) and write down 3-5 things you do repeatedly every day that are time-consuming, that you don't want to do but have to. For example:

• Checking through emails every morning

• Manually organizing meeting notes

• Checking data across various websites for weekly reports

• Replying to lots of similar-format messages

• Tracking project progress

These are the tasks your AI assistant will take over.

Tomorrow, we start building.

Preview: Day 2 — Quick Start

Tomorrow we're going hands-on. Whether you choose MyClaw Cloud (instant setup) or self-hosted (full control), you'll get your assistant running and send your first message.

See you tomorrow.

CloudClaw agents are generating significant buzz because they promise more practical functionality than standard AI chatbots. They don’t just answer questions; they can be configured to handle tasks like research, customer support, content creation, and daily operations. As interest rises, so does the confusion. Many people searching for lists of CloudClaw agents only find scattered documentation, app marketplaces, or community pages, with no concise explanation of what these agents actually do or how to get started. This guide breaks the topic down into clear categories, installation paths, and deployment options, making CloudClaw easier to understand.

What Are CloudClaw Agents and Why Is Search Interest Surging?

A CloudClaw agent is an AI assistant whose capabilities extend far beyond answering questions. It can be configured to handle tasks, execute multi-step processes, and work seamlessly with tools, files, or other systems. For example, an agent can assist with research, customer support, content workflows, or daily business operations. In short, it is a task-oriented AI tool built specifically to help people get real work done.

CloudClaw AI agents are gaining traction because they assist with actual work rather than just conversation. They can support research, customer support, content creation, and daily organizational management, making them highly beneficial for a wide variety of teams. As more people seek practical AI tools, interest in CloudClaw agents continues to grow.

CloudClaw Agents List by Use Case

• Efficiency and Daily Planning Agents These agents help with daily tasks such as summarizing, task tracking, and simple updates. Because their tasks are well-defined and their impact is immediate, they are often the easiest starting point. For teams experimenting with CloudClaw hosting, this is a highly practical first use case.

• Customer Support Agents Designed to answer FAQs, triage incoming tickets, and assist with routine replies, these agents are perfect for teams handling a high volume of repetitive inquiries daily.

• Research and Search Agents Research agents help gather information, summarize sources, and track key developments. They are ideal for teams that need quick access to useful data without spending hours on manual searches.

• Knowledge and Document Management Agents These agents assist teams in finding internal information, organizing notes, and supporting document workflows — especially useful when information is scattered across numerous files, tools, or pages.

• Content and Marketing Agents Content agents can draft blog posts, repurpose existing materials, and track trends. Marketing teams can also leverage them to support content planning and simple publishing workflows.

• Sales and Outreach Agents Sales-focused agents can help organize lead information, prepare follow-up content, and support contact management, proving highly effective at reducing repetitive manual work.

• Coding and Technical Workflow Agents Technical agents can support documentation writing, code reviews, monitoring, and other development tasks. They often deliver the most value when connected to the right tools and data sources

• CloudClaw, managed services like MyClaw offer an easier path to quickly start testing real-world agent use cases.)

• Communication and Email Agents These agents help triage messages, draft replies, and summarize conversations, saving massive amounts of time for teams managing heavy email volumes or internal communications.

Where to Find and Install CloudClaw Agents, Skills, and Templates

Currently, there is no single official store that houses all CloudClaw agents in one place. In most cases, setting up a CloudClaw agent involves starting from the main CloudClaw platform and adding the specific skills and connections required for your tasks.

• The best starting point is the official CloudClaw website and documentation. The homepage introduces the platform, while the agent overview explains how they work. For installation, the skill installation guides and ClawHub are the most practical resources to get started.

Simply put, many CloudClaw agents are built by combining skills, models, and channels, rather than downloading a complete agent with a single click. Some skills can be installed from ClawHub, others from GitHub, and some from local files.

Third-party app marketplaces and community directories can also help users discover ideas and templates. However, official resources are generally the safest starting point, especially when an agent requires access to messages, files, or business tools.

• Focus on the Underlying Skills: An agent’s name might sound impressive, but its true value comes from the skills it utilizes. A useful agent must have the right tools, data, and connections to actually complete its tasks.

• Consider the Use Case Environment: Some agents are better suited for internal team workflows, while others excel in customer support, content creation, or research. The configuration should match the environment where the agent will be deployed most frequently.

• Limit Access Initially: It is safer to start with limited permissions and a small-scale testing environment. This allows you to better understand how the agent operates before granting it access to more systems or sensitive information.

• Further Reading: CloudClaw vs. Claude Cowork: Which is Better for Real-World Automation?

How to Safely Deploy CloudClaw AI Agentsefer runol

ver settings, access permissions, and customization. This is a solid option for technical teams with the time to manag

curity as part of daily operations.

• Ma

  

  Services Make the First Step Easier For many teams, the hardest part isn’t choosing an agent, but getting CloudClaw running in a stable and straightforward way. This is where CloudClaw managed services like MyClaw fit in naturally. MyClaw is designed to help users run CloudClaw without the hassle of a full manual setup, allowing teams to onboard faster and explore common use cases like daily assistance, email workflows, research, and automation.

• Safe Deployment Starts Small A secure rollout typically begins with limited access and a small-scale test environment. It is best to connect only the strictly necessary tools, observe the agent’s behavior, and gradually expand. This approach minimizes errors and helps build trust before applying the agent to critical workflows.

Conclusion

The true value of CloudClaw agents lies in their ability to assist with real-world tasks, not just conversations. Often, the best approach is to build a simple agent for a specific job and gradually add more skills and connections over time. Official documentation and ClawHub are excellent starting points for configuration. For teams looking for a frictionless path, managed options like the CloudClaw managed service MyClaw make it easier to get the platform running and quickly begin testing practical agent ideas.

Today we’re announcing a partnership with VirusTotal, the world’s leading threat intelligence platform, to bring security scanning to ClawHub — OpenClaw’s skill marketplace.

TL;DR: All skills published to ClawHub are now scanned using VirusTotal’s threat intelligence, including their new Code Insight capability. This provides an additional layer of security for the OpenClaw community.

Why This Matters

For the past 20 years, security models have been built around locking devices and applications down — setting boundaries between inter-process communications, separating internet from local, sandboxing untrusted code. These principles remain important.

But AI agents represent a fundamental shift.

Unlike traditional software that does exactly what code tells it to do, AI agents interpret natural language and make decisions about actions. They blur the boundary between user intent and machine execution. They can be manipulated through language itself.

We understand that with the great utility of a tool like OpenClaw comes great responsibility. Done wrong, an AI agent is a liability. Done right, we can change personal computing for the better.

OpenClaw skills are powerful. They extend what your AI agent can do — from controlling smart home devices to managing finances to automating workflows. But with that power comes risk.

Skills are code that runs in your agent’s context, with access to your tools and your data. A malicious skill could:

• Exfiltrate sensitive information

• Execute unauthorized commands

• Send messages on your behalf

• Download and run external payloads

As the OpenClaw ecosystem grows, so does the attack surface. We’ve already seen documented cases of malicious actors attempting to exploit AI agent platforms. We’re not waiting for this to become a bigger problem.

How It Works

When a skill is published to ClawHub:

1. Deterministic Packaging — The skill files are bundled into a ZIP with consistent compression and timestamps, along with a _meta.json containing publisher info and version history

2. Hash Computation — A SHA-256 hash is computed for the entire bundle, creating a unique fingerprint

3. VirusTotal Lookup — The hash is checked against VirusTotal’s database. If the file exists with a Code Insight verdict, results are returned immediately

4. Upload & Analysis — If not found (or no AI analysis exists), the bundle is uploaded to VirusTotal for fresh scanning via their v3 API

5. Code Insight — VirusTotal’s LLM-powered Code Insight (powered by Gemini) performs a security-focused analysis of the entire skill package, starting from SKILL.md and including any referenced scripts or resources. It doesn’t just look at what the skill claims to do — it summarizes what the code actually does from a security perspective: whether it downloads and executes external code, accesses sensitive data, performs network operations, or embeds instructions that could coerce the agent into unsafe behavior

6. Auto-Approval — Skills with a “benign” Code Insight verdict are automatically approved. Anything flagged as suspicious is automatically marked with a warning. Skills flagged as malicious are instantly blocked from download

7. Daily Re-scans — All active skills are re-scanned daily to detect if a previously clean skill becomes malicious

Scan results are displayed on every skill page and in version history, with direct links to the full VirusTotal report.

VirusTotal already protects the Hugging Face ecosystem using hash-based lookups against their threat intelligence database. Our integration goes further — we upload full skill bundles for Code Insight analysis, giving the AI a complete picture of the skill’s behavior rather than just matching known signatures.

What This Is — And What It Isn’t

Let’s be clear: this is not a silver bullet.

VirusTotal scanning won’t catch everything. A skill that uses natural language to instruct an agent to do something malicious won’t trigger a virus signature. A carefully crafted prompt injection payload won’t show up in a threat database.

What this does provide:

• Detection of known malware — Trojans, stealers, backdoors, malicious payloads

• Behavioral analysis — Code Insight identifies suspicious patterns even in novel threats

• Supply chain visibility — Catching compromised dependencies and embedded executables

• A signal of intent — We’re investing in security, and this is the first of many layers

Security is defense in depth. This is one layer. More are coming.

The Bigger Picture

This partnership is part of a broader security initiative at OpenClaw. In the coming days, we’ll be publishing:

• A comprehensive threat model for the OpenClaw ecosystem

• A public security roadmap tracking defensive engineering goals

• Details on our security audit covering the entire codebase

• A formal security reporting process with defined SLAs

Follow progress and read the full security program overview at trust.openclaw.ai.

We’ve brought on Jamieson O’Reilly (founder of Dvuln, co-founder of Aether AI, CREST Advisory Council member) as lead security advisor to guide this program.

AI agents that take real-world actions deserve real security processes. We’re building them.

For Skill Publishers

If you publish skills to ClawHub, your code will now be scanned automatically. Here’s how it works:

1. Your skill is published and the VT scan runs asynchronously

2. If the scan returns a “benign” verdict, your skill is automatically approved

3. If something is flagged as suspicious, your skill is marked with a warning but remains available for transparency

4. If flagged as malicious, your skill is instantly blocked from download

5. You can check scan status on your skill’s detail page with a direct link to the full VirusTotal report

We expect some false positives initially — security tooling isn’t perfect. If your skill is incorrectly flagged, reach out to us at security@openclaw.ai and we’ll review it.

For Users

When browsing ClawHub, you’ll see scan status for each skill. This gives you one more data point when deciding what to trust. But remember:

• A clean scan doesn’t mean a skill is safe

• Always review what permissions a skill requests

• Start with skills from publishers you trust

• Report suspicious behavior to security@openclaw.ai

Thank You, VirusTotal

We’re grateful to Bernardo Quintero and the VirusTotal team for their partnership. Their platform protects millions of users every day, and we’re proud to bring that protection to the OpenClaw community.

What’s Next

This is the beginning, not the end. We’re committed to making OpenClaw the most secure AI agent platform available. Expect more announcements soon.

The lobster grows stronger. 🦞

Questions about security? security@openclaw.ai

Publish skills: clawhub.ai

Join the discussion: Discord

— Peter, Jamieson, and Bernardo