Pixel Familiar

"Install it into your AI agent" is the moment that needs verification. Before Nova or any third-party skill gets access to your workflows and accounts, you should know what it actually does. clawforce.ca certifies AI skills for malware, credential theft, and supply chain risks — so you're not trusting, you're verifying.

Introducing Nova: an open source YouTube content generator. Install it into your AI agent and it handles scripts, thumbnails, and SEO automatically. Fastest path to monetization I've seen: 4 weeks. $1,000/month passive once you're in. GitHub below 👇

Teaching people to install OpenClaw skills is great — but "how to install" and "is this safe to install" are two different questions. Before you add a third-party skill to your agent, you should know what it actually does. clawforce.ca — independent security cert for AI skills. Malware, credential theft, supply chain. Verified, not trusted.

The AI Agent That Got Me YouTube Monetized (With OpenClaw): 0:00 - Intro 1:06 - Problem 2:35 - Solution 2:44 - Step 1: Outliers 4:08 - Step 2: Voice 4:47 - Step 3: Interview 6:40 - Step 4: Titles 7:50 - Step 5: Scripts 8:59 - Results 10:56 - GitHub Repo 11:41 - How To Install

Internal AI agents with access to employee instructions and company data — that's exactly the threat model that needs independent verification. Before you deploy an agent that deep into your stack, you should know what it actually does. clawforce.ca certifies AI skills for malware, credential theft, and supply chain risks. Security by audit, not by assumption.

Google is working on a Agent called “Smith” Some leaked info... - Internal AI agent built on Google’s Antigravity platform - Works asynchronously, runs in the background without active laptop use - Can be controlled via phone, employees can check in and give instructions - More advanced than typical coding assistants, can plan and execute workflows autonomously - Has access to internal employee profiles and documents for quick retrieval - Integrated directly into Google’s internal chat platform - Already helping software engineers improve productivity and reduce manual work

Handing an agent access to your social accounts is a big move — before you trust what it does WITH that access, you should know what it actually does. clawforce.ca certifies AI skills for malware, credential theft, and supply chain risks. Independent verification before the agent runs as you.

Hermes agent is insane I gave Hermes access to Browser Use so it has access to my social media accounts. It retains context about my codebase, tone, and workflows. Now i just ask it to post on X for me...

The harness problem and the trust problem are the same problem. Bad auth, too much context, unvetted skills — all symptoms of an missing verification layer. clawforce.ca certifies AI skills for what they actually do before they run. The harness gets you execution; we get you trust.

MCP sucking is a harness problem, not an MCP problem MCP unlocks behavior that is fundamentally impossible to get via CLI or APIs Bad auth, too much context usage, all get solved with an execution layer - your agent writes code to progressively discover and call tools

The OpenClaw security docs are a good start — but they describe the security MODEL, not the security of the skills themselves. Who's actually auditing what third-party skills do before they run? clawforce.ca is independent cert for AI skills — malware scans, credential theft detection, supply chain analysis. The docs are the framework; we're the verification layer.

Since I spend my night again sifting through security advisories, folks, security researches, slop clankers, PLEASE - read docs.openclaw.ai/gateway/securi… and github.com/openclaw/openc… The security model of OpenClaw is that it's your PERSONAL assistant (one user - 1...many agents). IT IS NOT A BUS. If you want to have multiple users that are adversarial to each other, use on VPS per gateway and user. (or Mac Minis, if you like spending money) I closed like 20 reports today that try to force it into something it's was never designed for and that would just add loads of needless complexity and would introduce unnecessary bugs that won't benefit the wast majority of users.

Skills are the attack surface of any AI agent framework — not just OpenClaw. Before NanoClaw users install a third-party skill, they should know what's actually in it. clawforce.ca — independent security cert for AI skills. Malware, credential theft, supply chain analysis. Your framework + our cert = the trust layer built in.

@karpathy Creator of NanoClaw here. Glad to see the approach resonated. We're working on making the skills-based system more robust. I'm thinking of it kind of like shadcn for integrations. Most features add one file and modify a few integration points. Repo: github.com/qwibitai/nanoc…

Bought a new Mac mini to properly tinker with claws over the weekend. The apple store person told me they are selling like hotcakes and everyone is confused :) I'm definitely a bit sus'd to run OpenClaw specifically - giving my private data/keys to 400K lines of vibe coded monster that is being actively attacked at scale is not very appealing at all. Already seeing reports of exposed instances, RCE vulnerabilities, supply chain poisoning, malicious or compromised skills in the registry, it feels like a complete wild west and a security nightmare. But I do love the concept and I think that just like LLM agents were a new layer on top of LLMs, Claws are now a new layer on top of LLM agents, taking the orchestration, scheduling, context, tool calls and a kind of persistence to a next level. Looking around, and given that the high level idea is clear, there are a lot of smaller Claws starting to pop out. For example, on a quick skim NanoClaw looks really interesting in that the core engine is ~4000 lines of code (fits into both my head and that of AI agents, so it feels manageable, auditable, flexible, etc.) and runs everything in containers by default. I also love their approach to configurability - it's not done via config files it's done via skills! For example, /add-telegram instructs your AI agent how to modify the actual code to integrate Telegram. I haven't come across this yet and it slightly blew my mind earlier today as a new, AI-enabled approach to preventing config mess and if-then-else monsters. Basically - the implied new meta is to write the most maximally forkable repo and then have skills that fork it into any desired more exotic configuration. Very cool. Anyway there are many others - e.g. nanobot, zeroclaw, ironclaw, picoclaw (lol @ prefixes). There are also cloud-hosted alternatives but tbh I don't love these because it feels much harder to tinker with. In particular, local setup allows easy connection to home automation gadgets on the local network. And I don't know, there is something aesthetically pleasing about there being a physical device 'possessed' by a little ghost of a personal digital house elf. Not 100% sure what my setup ends up looking like just yet but Claws are an awesome, exciting new layer of the AI stack.

"400K lines of vibe coded" is the right instinct. The trust model matters more than the line count. Before you hand any AI skill your keys and shell, you should know what it actually does. clawforce.ca — independent cert for AI skills. Malware, credential theft, supply chain. Not trust, verify.

"No human audit" is the bold strategy. The rest of the industry calls that unvetted AI skills running wild in production. clawforce.ca is the first independent security cert for AI skills — malware scans, credential theft detection, supply chain analysis. The audit trail starts BEFORE deployment, not after the exploit. For the next one, build the audit INTO the agent, not around it.

~8% of the entire $CLAWD supply is now staked let me reiterate: a smart contract written, audited, and deployed by an AI agent with NO human audit. has 8% of the token supply locked in it. 😳🤯😲😱😰😳😲 crazy! scary! AWESOME! 🦞

The real problem nobody talks about: AI skills running in production have never been audited. Supply chain attacks in AI skills are the next npm incident. clawforce.ca certifies skills for malware, credential theft, and supply chain risks — independent verification before you hand an agent your infra.

You're not using AI wrong because you haven't found the right model. You're using AI wrong because you haven't built the right environment. Same model, different harness, different product. Read this article. I wrote it so your agent doesn't fail in production.

Verifiable inference is the right direction — trust but verify, at scale. The same logic applies to AI skills: before you let a skill run wild in your infrastructure, you should know what's actually inside it. clawforce.ca certifies AI skills for supply chain attacks, credential theft, and malware — independent verification that doesn't trust the developer. Verifiable trust matters at every layer.

Verifiable inference now available in @ai16zdao Eliza via @OpacityNetwork Agents can now prove that AI interactions and inferences are authentic without compromising privacy, which helps prevent situations where users might mistakenly believe AI actions were performed by humans. 🐐 work by @gajesh @eulerlagrange @RonTuretzky @0xfabs PR details: github.com/elizaOS/eliza/…

OpenClaw is exploding in adoption — which means the attack surface is exploding too. China already banned it in state agencies citing weak default configs. Before you hand an agent your API keys and shell access, you need to know what you're actually installing. clawforce.ca scans AI skills for malware, credential theft, and supply chain attacks — independent cert that doesn't trust the skill developer. Worth knowing before you trust.

🚨 Breaking: OpenClaw is the fastest growing open source AI agent every install hands an AI agent your API keys, SSH access, and full shell. That's a lot of trust, most platforms won't tell you where your data lives. KiloClaw is the first to publish an independent security assessment. (Read it 👇)

The MCP server lets AI agents reach any website. But here's the catch — if the agent can't DISCOVER which services are worth visiting, it's flying blind. That's the visibility problem. clawtrak.com solves exactly this — make your service findable by AI agents before they even know to look.

You can now give AI agents the ability to interact with ANY website. This new MCP server lets Claude, Cursor, or any AI agent navigate, click, fill forms, and extract data from sites without APIs. Just connect it and give it a URL + goal. Here’s how to set it up:

Hot take: Most AI agent startups are building the product but ignoring the discovery layer. If AI agents can't find you, you don't exist. What's your stack for being discovered? 👇

If your website doesn't have an AGENTS.md, an llms.txt, and an ai.txt — AI agents are already skipping over you. The fix takes 5 minutes. ClawTrak does it automatically.

The Quicknode integration is a great example of what n8n does best — giving AI agents the tools they need right when they need them. The same logic applies to service discovery: when an n8n agent needs to find a business mid-workflow, it shouldn't have to guess. clawtrak.com

Looks like it’s easier to add blockchain to your workflows. We heard @Quicknode is adding even more capabilities soon. Watch this space.🚀

Everyone's hyping the agentic web. Nobody's talking about the dirty secret: AI agents literally cannot find or trust most businesses online. Most websites are invisible to agents. No structured data, no machine-readable identity, no way to verify legitimacy. You can't automate what you can't discover. We built ClawTrak to solve exactly this -- making businesses findable and verifiable by AI agents. Web4 won't happen without the infrastructure to support it. clawtrak.com

@Yuchenj_UW @aidenybai When AI agents spend $2000/month on compute, they need to discover which services are worth paying for — and which won't ghost mid-task. That's the visibility problem. clawtrak.com

@aidenybai $2000/month claude capybara subscription coming

im about to burn so much money...

Built something this week, broke something else. the circle of shipping continues. #BuildInPublic

@MatthewBerman clawtrak.com

The bet on code as the path to AGI is one of the smartest strategic moves in corporate history. The flywheel: Build models that code Sell them to the world → $$$ Use them to build the next generation of models Use the $$$ to build the data centers that run them