Build a Daily Brand Radar Agent with OpenClaw and BrowserMan

Most brand monitoring starts as a messy habit.

Someone opens Google. Then X. Then LinkedIn. Then Reddit. Then Product Hunt. Then a few competitor sites. Maybe they paste notes into a doc. Maybe they forget tomorrow.

This is exactly the kind of workflow an AI agent should own.

Not because the agent is smarter than a marketer. Because the workflow is repetitive, browser-heavy, and evidence-based: search, open, inspect, save links, compare changes, and summarize what matters.

This guide shows how to build a simple daily brand radar agent with OpenClaw and BrowserMan.

The example below is written for a SaaS or AI tools brand. If you run a devtool, AI app, agency, marketplace, or early-stage startup, you can adapt the same setup in a few minutes.

What the agent will do

Every morning, the agent should be able to:

1. Search Google for your brand and target competitors.
2. Find the official website and major social profiles.
3. Check fresh mentions across search results and public social pages.
4. Inspect competitor websites, pricing pages, docs, changelogs, and launches.
5. Save source URLs and excerpts.
6. Send a short report at 8:00 AM.

The output should be practical, not a generic AI summary:

Daily Brand Radar — 2026-04-29

1. Important mentions
- ...

2. Competitor changes
- ...

3. Social signals
- ...

4. Opportunities
- ...

5. Recommended action today
- ...

Step 1: Choose your OpenClaw setup

You need somewhere for the agent to run.

Option A: Use ClawMama for the fastest setup

If you want the lowest-friction path, use ClawMama.

ClawMama is a hosted OpenClaw option. Instead of managing a server, runtime, storage, and bot process yourself, you can create an OpenClaw bot from Telegram and start using it quickly.

Typical setup flow:

1. Open clawmama.run.
2. Start the ClawMama bot on Telegram.
3. Create a bot token with BotFather.
4. Send /create to ClawMama.
5. Paste the BotFather token.
6. Choose a template.
7. Let ClawMama deploy the OpenClaw bot for you.

This is the path I would recommend for non-infrastructure users, marketers, founders, and operators who want a working agent before they want a server project.

Option B: Install OpenClaw yourself

If you prefer to run the agent yourself, use OpenClaw directly.

Start from the official site and docs:

• OpenClaw: https://openclaw.ai
• OpenClaw docs: https://docs.openclaw.ai
• GitHub: https://github.com/openclaw/openclaw

Self-hosting is better if you want deeper control over runtime, model providers, storage, permissions, and deployment environment.

Step 2: Install BrowserMan and connect your real browser

Next, give the agent a browser it can actually use.

Go to browserman.run and install the BrowserMan Chrome extension.

BrowserMan connects your real Chrome browser to an AI agent. That matters because brand research often depends on the real web:

• Google results,
• X and LinkedIn pages,
• logged-in dashboards,
• social platforms,
• competitor pages,
• docs and changelogs,
• communities and forums.

BrowserMan's important security model is delegated access:

• the agent gets scoped browser access,
• your cookies stay in your browser,
• you do not paste passwords into chat,
• you can audit what happened,
• you can revoke access.

After installing the extension:

1. Sign in to BrowserMan.
2. Pair your Chrome browser.
3. Confirm the browser appears in your BrowserMan dashboard.
4. Keep Chrome online when you want scheduled tasks to run.

If you are using the BrowserMan CLI locally, the basic commands are:

npm install -g browserman-cli
browserman setup
browserman doctor
browserman browser ping --json

If you do not want a global install, use npx:

npx -y browserman-cli setup
npx -y browserman-cli doctor
npx -y browserman-cli browser ping --json

Step 3: Add BrowserMan access to your OpenClaw agent

OpenClaw can use skills to teach an agent how to operate external tools.

For skill discovery and installation, use ClawHub or OpenClaw's skills system:

npx -y clawhub search browserman
npx -y clawhub install <browserman-skill-slug>
openclaw skills list
openclaw skills check

If your OpenClaw workspace already includes a BrowserMan skill, you can also use it directly. The key requirement is not the exact installer path; it is that the agent knows the BrowserMan operating rules:

• check the BrowserMan script catalog first,
• confirm the browser is online,
• use optimized scripts when available,
• fall back to browser control for unmapped sites,
• never ask the user for passwords or cookies,
• keep externally visible actions explicit and auditable.

A working BrowserMan connection should pass a ping:

browserman browser ping --json

For Google search through BrowserMan scripts, the pattern looks like this:

browserman script run \
  --site google.com \
  --action search \
  --text "BrowserMan AI agent browser automation" \
  --wait \
  --json

For X posting or reading, use BrowserMan's X scripts only when your browser is connected and you have intentionally granted access.

Step 4: First prompt — discover the brand footprint

Now give the agent a concrete research task.

For an English SaaS or AI tools brand, use this prompt:

You are my brand radar agent.

Brand: [Brand name]
Website if known: [website or unknown]
Category: [AI tool / devtool / SaaS / marketplace / agency]
Competitors: [optional list]

Task:
Use BrowserMan and Google Search to discover the brand's official website, docs, blog, changelog, pricing page, and public social profiles.

Search queries to run:
1. "[Brand name] official website"
2. "[Brand name] X Twitter"
3. "[Brand name] LinkedIn"
4. "[Brand name] GitHub"
5. "[Brand name] Product Hunt"
6. "[Brand name] Reddit"
7. "[Brand name] alternatives"
8. "[Brand name] pricing"

Output a table with:
- source type
- title
- URL
- confidence level
- why you think it is official or relevant
- notes

Rules:
- Save raw search results before summarizing.
- Do not invent links.
- Separate official links from third-party mentions.
- Flag uncertain results instead of guessing.

The first output should be a footprint map:

Type	URL	Confidence	Notes
official site	...	high	domain matches brand
blog	...	high	linked from official site
X profile	...	medium	handle matches, needs verification
GitHub	...	high	linked from docs
Product Hunt	...	medium	launch page found
competitor mention	...	low	third-party comparison

This map becomes the source list for the daily radar.

Step 5: Second prompt — find competitors and social surfaces

Once the brand footprint is known, ask the agent to expand the map.

Using the verified brand footprint from the previous step, build a competitor and social-signal map.

Use Google Search and BrowserMan to find:
1. Direct competitors.
2. Alternative products mentioned in search results.
3. Comparison pages.
4. Review sites.
5. Community discussions.
6. Social profiles for the brand and top competitors.
7. Product Hunt, GitHub, docs, changelog, and pricing pages where relevant.

Prioritize sources that can change over time:
- pricing pages
- changelogs
- launch pages
- docs pages
- X profiles
- Reddit discussions
- review pages
- comparison pages

Output:
1. Competitor table.
2. Source watchlist.
3. Search queries to repeat daily.
4. Risks and caveats.

Rules:
- Keep source URLs.
- Do not treat SEO listicles as truth without cross-checking.
- Mark each competitor as direct, adjacent, or noisy.

A useful competitor table looks like this:

Competitor	Type	Evidence	Pages to watch	Why it matters
Competitor A	direct	appears in comparison pages	pricing, changelog, docs	same buyer
Competitor B	adjacent	appears in Reddit alternatives	blog, X, launch page	same workflow
Competitor C	noisy	SEO article mention only	none yet	weak signal

Step 6: Third prompt — schedule the daily 8 AM report

Now turn the research into a recurring operating loop.

If your OpenClaw setup supports scheduled prompts or heartbeat-style automation, create a daily task for 8:00 AM in your timezone.

Use this prompt:

Every day at 8:00 AM [timezone], run my Daily Brand Radar.

Brand: [Brand name]
Primary site: [URL]
Known social profiles:
- X: [URL]
- LinkedIn: [URL]
- GitHub: [URL]
- Product Hunt: [URL]

Competitors to monitor:
- [Competitor 1]
- [Competitor 2]
- [Competitor 3]

Daily task:
1. Use BrowserMan to run Google searches for fresh mentions from the last 24-48 hours.
2. Check the brand's known website, blog, docs, changelog, and social profiles.
3. Check competitor pricing pages, changelogs, launch pages, docs, and social profiles.
4. Look for new comparisons, complaints, customer questions, launches, and positioning changes.
5. Save source URLs and short excerpts.
6. Prepare a concise report.

Report format:
Daily Brand Radar — [date]

1. Important mentions
- Include URL and why it matters.

2. Competitor changes
- Pricing, product, messaging, launch, docs, or social movement.

3. Customer/community signals
- Repeated questions, complaints, objections, or language.

4. Opportunities
- Reply opportunity, content idea, landing-page improvement, SEO topic, or product insight.

5. Recommended action today
- One concrete action, not a generic suggestion.

Rules:
- Do not fabricate changes.
- If nothing meaningful changed, say "No material change".
- Keep the report short.
- Include links for every claim.
- Ask before posting publicly unless I have granted standing authorization.

For the first week, keep the watchlist small. Three competitors and five to ten source pages are enough. The goal is a reliable habit, not a giant brittle crawler.

Step 7: Make the report better over time

The first report will be basic. That is fine.

Improve the system by adding memory:

• known official links,
• known competitors,
• recurring search queries,
• sources that are noisy,
• sources that produce useful signals,
• previous day's report,
• actions already taken.

The agent should compare today against yesterday.

A good recurring instruction is:

Before writing today's report, read yesterday's report and the source watchlist. Do not repeat old items unless there is a new development. If a source was noisy three days in a row, lower its priority.

This turns the agent from a one-off researcher into an operator.

What to monitor for different brands

For an AI or SaaS brand, monitor:

• competitor changelogs,
• pricing pages,
• docs updates,
• Product Hunt launches,
• GitHub releases,
• Reddit alternatives threads,
• X posts from founders and users,
• integration pages,
• comparison pages.

For a marketplace or ecommerce brand, monitor:

• marketplace search results,
• product reviews,
• creator posts,
• TikTok and YouTube comments,
• competitor stores,
• pricing and promotions,
• customer complaints,
• seasonal keyword shifts.

For an agency or services brand, monitor:

• client vertical keywords,
• competitor case studies,
• LinkedIn posts,
• review pages,
• search ads and landing pages,
• industry newsletters,
• hiring pages.

The setup is the same. Only the source map changes.

Why BrowserMan is useful here

A daily brand radar agent needs to use the web like a human operator:

• search Google,
• open result pages,
• inspect social profiles,
• read dynamic pages,
• use logged-in sessions when needed,
• collect screenshots or source snippets,
• move findings into a report.

That is hard to do with a chat-only model.

BrowserMan gives the agent a real browser session without giving away your passwords. OpenClaw gives the agent a workspace, memory, files, and scheduling pattern. ClawMama makes the OpenClaw side easier if you do not want to manage infrastructure.

Together, they let you build a small but useful operator:

Every morning, read the real web and tell me what changed.

That is a better use of agents than asking for generic brand advice from a blank prompt.