How to Make an OpenClaw or Hermes Agent Check Your Competitors Every Week

Reader persona: a founder, operator, marketer, or small team lead who needs a lightweight competitor watch system.

Job to be done: turn “keep an eye on competitors” into a repeatable weekly agent workflow with sources, citations, and human review.

Most competitor research fails because it is too broad.

A vague prompt like this rarely helps:

Research our competitors and tell me what they are doing.

It usually produces a generic summary. It may be out of date. It may miss the pages that actually changed.

A better approach is narrower:

Every week, check the same competitor sources, detect what changed, summarize what matters, cite the evidence, and ask me before taking any external action.

That is a good job for an OpenClaw or Hermes agent.

The agent is not just chatting. It can keep a file, visit pages, compare notes, run on a schedule, and report back with links.

What the agent should monitor

Start with pages where competitors reveal real movement:

• homepage headline;
• pricing page;
• product changelog;
• docs landing page;
• blog or announcements;
• integrations page;
• job listings;
• status page;
• public GitHub repo, if relevant;
• X, LinkedIn, or community posts, if allowed and accessible.

Do not start with “the whole internet.”

Start with 3–5 competitors and 5–8 URLs per competitor.

That is enough to get useful signal without drowning in noise.

Step 1: Create the competitor watch file

Ask the agent to create a file like this:

# Competitor Watchlist

## Competitor A
- Homepage: https://example.com/
- Pricing: https://example.com/pricing
- Changelog: https://example.com/changelog
- Docs: https://docs.example.com/

## Competitor B
- Homepage: https://example.ai/
- Pricing: https://example.ai/pricing
- Blog: https://example.ai/blog
- Integrations: https://example.ai/integrations

## Rules
- Cite every claim with a URL.
- Label confidence as high, medium, or low.
- Do not scrape private pages.
- Respect terms, privacy, robots, and rate limits.
- Do not post, message, purchase, or sign up without approval.

This file becomes the agent’s stable input.

Step 2: Give the agent a narrow weekly task

Use a prompt like this:

You are my weekly competitor watch agent.

Use the competitor watchlist file.

For each competitor:
1. open the listed public pages;
2. compare them with last week's notes if available;
3. identify meaningful changes;
4. ignore cosmetic changes unless they affect positioning, pricing, features, or go-to-market;
5. cite every claim with a URL;
6. label confidence as high, medium, or low;
7. write a short operator-ready summary.

Do not create accounts.
Do not bypass paywalls.
Do not scrape private data.
Do not post or contact anyone.
If a page blocks access, report that clearly.

This is much stronger than asking for a general market report.

The agent has a job, sources, constraints, and output rules.

Step 3: Define the output format

Ask for the same structure every week:

# Weekly Competitor Watch — YYYY-MM-DD

## Executive summary
- 3–5 bullets on what changed and why it matters.

## High-signal changes

### Competitor A
- Change:
- Evidence:
- Why it matters:
- Confidence:

### Competitor B
- Change:
- Evidence:
- Why it matters:
- Confidence:

## Pricing / packaging movement

## Messaging movement

## Product / integration movement

## Recommended follow-up
- What we should inspect next.
- What we should not overreact to.

## Source list
- URL list checked.

This makes the report easy to compare over time.

Step 4: Store last week’s notes

The agent should save each report in a folder:

competitor-watch/
  2026-05-02.md
  2026-05-09.md
  2026-05-16.md

The next run should compare against the latest previous report.

That is where the agent becomes more useful than a one-off chat.

It remembers the operating context through files.

Step 5: Add human review

Competitor monitoring can easily become noisy.

Ask the agent to separate facts from interpretation:

Before making recommendations, separate:
1. observed facts;
2. likely interpretation;
3. recommended action;
4. confidence level.

Example:

Observed fact:
Competitor A added an “Enterprise” plan to its pricing page.

Evidence:
https://example.com/pricing

Interpretation:
They may be moving upmarket.

Confidence:
Medium. The pricing page changed, but there is no launch post yet.

Recommended action:
Review our enterprise messaging and collect 3 customer objections from recent calls.

This keeps the agent honest.

Step 6: Use BrowserMan only when browser access matters

Some public pages are easy to fetch. Others require a real browser because they use client-side rendering, dashboards, or login-based views.

If the task needs browser access, BrowserMan can let the agent inspect pages in a controlled real browser session.

Use it for:

• pages that do not render in simple fetches;
• visual comparison;
• logged-in dashboards you explicitly approve;
• checking public web apps;
• collecting screenshots for internal review.

Keep the safety boundary clear:

The agent may open, read, and summarize.
The agent may not post, purchase, sign up, delete, or message without approval.

BrowserMan is useful because it gives the agent controlled access to a real browser, while high-risk actions can stay behind human approval.

Step 7: Run it from ClawMama

If you already run OpenClaw or Hermes, create this workflow in your own environment.

If you do not want to maintain the agent runtime first, create a ClawMama agent:

https://t.me/clawmamarun_bot

ClawMama gives you a managed OpenClaw or Hermes agent. New users get $2 of AI credits and access to the latest ChatGPT model, so you can test a workflow before building your own infrastructure around it.

A good first message is:

Help me build a weekly competitor watch workflow.

First, create a competitor watchlist file.
Then ask me for 3 competitors and the URLs to monitor.
Then run the first report.
Save the report as a dated markdown file.
Do not contact anyone or take external actions without approval.

That gives the agent a useful starting shape.

What good output looks like

A good report is short and evidence-based:

# Weekly Competitor Watch — 2026-05-02

## Executive summary
- Competitor A appears to be moving upmarket after adding an Enterprise plan.
- Competitor B changed homepage messaging from “AI assistant” to “AI operations platform.”
- Competitor C launched a new Slack integration.

## High-signal changes

### Competitor A
- Change: Added Enterprise plan.
- Evidence: https://example.com/pricing
- Why it matters: possible sales-led motion.
- Confidence: high.

## Recommended follow-up
- Review our enterprise objections.
- Update sales discovery questions.
- Do not change pricing yet; wait for one more signal.

That is more useful than a long market essay.

Final takeaway

A weekly competitor agent should not try to “know the market.”

It should do a narrower job:

check known sources → detect changes → cite evidence → summarize implications → ask before acting

That is where OpenClaw, Hermes, ClawMama, and BrowserMan are practical.

They turn a vague research habit into a repeatable workflow.